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Plasmonic substrates have been extensively investigated due to their potential applications in fluorescence microscopy, chemical sensing, and photochemical reactions. The optical properties of the substrate depend on the spatial and temporal features of the plasmon excited. Hence, the ability to directly visualize plasmon dynamics is crucial. In this study, we investigated the spatial and temporal properties of plasmon excitation in a plasmonic nanobowl substrate consisting of a periodic hexagonal array of nanoscale bowl-like structures developed with self-assembly. Near-field transmission imaging revealed that multiple plasmon resonance bands are observed from visible to near-infrared spectral region, and the optical contrast of the image is dependent on the observed band. Near-field two-photon photoluminescence microscopy revealed that the probability of excitation inside each nanoscale bowl-like structure is greater than that in the surrounding area. Near-field time-resolved imaging revealed that the nanobowl substrate exhibited a substantially long plasmon dephasing time, exceeding 12 fs. Based on the spectral features of the near-field and far-field spectra, we found that optically dark plasmon mode is excited by the near-field illumination and only partly contributes to the long dephasing time observed. This fact indicates that the dephasing time is extended by some other mechanism in the periodic substrate. We revealed from this study that the enhanced optical fields induced in the nanobowl structure originate from the photosynergetic effect of the cavity mode and plasmon mode excited. [ABSTRACT FROM AUTHOR]

Purpose: Compared with lower field strengths, DWI at 7 T faces the combined challenges of increased distortion and blurring due to B0 inhomogeneity, and increased signal dropouts due to B1+ inhomogeneity. This study addresses the B1+ limitations using slice‐specific static parallel transmission (pTx) in a multi‐shot, readout‐segmented EPI diffusion imaging sequence. Methods: DWI was performed in 7 healthy subjects using MRI at 7 T and readout‐segmented EPI. Data were acquired with non‐pTx circular‐polarized (CP) pulses (CP‐DWI) and static pTx pulses (pTx‐DWI) using slice‐specific B1+ shim coefficients. Each volunteer underwent two scan sessions on the same day, with two runs of each sequence in the first session and one run in the second. The sequences were evaluated by assessing image quality, flip‐angle homogeneity, and intrasession and intersession repeatability in ADC estimates. Results: pTx‐DWI significantly reduced signal voids compared with CP‐DWI, particularly in inferior brain regions. The use of pTx also improved RF uniformity and symmetry across the brain. These effects translated into improved intrasession and intersession repeatability for pTx‐DWI. Additionally, re‐optimizing the pTx pulse between repeat scans did not have a negative effect on ADC repeatability. Conclusion: The study demonstrates that pTx provides a reproducible image‐quality increase in multishot DWI at 7 T. The benefits of pTx also extend to quantitative ADC estimation with regard to the improvement in intrasession and intersession repeatability. Overall, the combination of multishot imaging and pTx can support the development of reliable, high‐resolution DWI for clinical studies at 7 T. [ABSTRACT FROM AUTHOR]

To realize optical image encryption for long-distance transmission while considering its security performance, an optical image encryption scheme is proposed in this paper. In the scheme, the pixel information of the plaintext image is first encoded by orbital angular momentum (OAM) holograms; then, the information-coded OAM beam is transmitted through a 1 km multimode fiber to generate speckles as ciphertexts for encryption; and finally, a pre-trained deep learning model capable of learning the relationship between the output speckles and the input information-coded OAM modes is used for decryption. The proposed scheme is not only able to achieve high fidelity recovered image but also a remarkable level of security. The high security stems from the combined use of three keys: the order key, the model key, and the coder key, during optical encryption. The image can therefore only be decrypted by authorized users who simultaneously know the three keys. We have experimentally demonstrated the high fidelity and high security encryption/decryption capabilities. Our work can provide a promising avenue for further research into long-distance optical image transmission and encryption with ultra-high security. [ABSTRACT FROM AUTHOR]

In today's digitally connected world, the protection of privacy and data security in open communication media (OCM) is paramount. As digital devices become more widespread and increase in global connectivity, the significance of image encryption has reached unprecedented levels. Traditional encryption techniques often fall short when applied to images due to their unique properties such as high correlation and large data quantities. To address these challenges, this paper presents a novel image encryption method that integrates principles from deoxyribonucleic acid (DNA) rules, the logistic map, and a hyperchaotic model with memcapacitors. The intricate and unpredictable nature of the memcapacitor‐based hyperchaotic system, coupled with deficiencies in current image encryption algorithms, serves as a catalyst for the development of this new algorithm. The proposed encryption strategy leverages the encoding properties of DNA and the complex dynamics of hyperchaotic systems to achieve enhanced image encryption. Through simulations and evaluations using reference images, the effectiveness of the method is demonstrated. It surpasses current techniques in terms of statistical robustness, resistance to brute‐force attacks, and protection against differential attacks. The research concludes that combining DNA principles, logistic maps, and memcapacitor‐based hyperchaotic systems significantly improves image encryption. This approach enhances data security for image transmission in open communication channels, addressing the limitations of traditional encryption techniques. As digital connectivity expands globally, the demand for robust image encryption is expected to increase, making this research pivotal in establishing standards for future advancements in image encryption algorithms. [ABSTRACT FROM AUTHOR]

The advancement of 6G (6th Generation Mobile Networks) communication technology has posed challenges for traditional communication network architectures in meeting the demands for communication efficiency and quality. Semantic communication technology, characterized by its "understand before transmit" approach, has emerged as a pivotal technology driving the progress of 6G due to its ability to enhance communication efficiency and quality. The Wireless Image Transmission Transformer (WITT) model, which operates as a semantic communication system leveraging vision transformer technology for the transmission of semantic images, has shown efficacy in transmitting input images through processes of feature extraction and channel adaptation. This study introduces an advanced channel adaptive module that is informed by deep learning methodologies and the adaptive modulation principles of the Variational Information Bottleneck (VIB). This innovation enhances the original WITT model, resulting in the development of the Adaptive Wireless Image Transmission Transformer (ADWITT) architecture. Comprehensive experimental results have unequivocally shown that the transmission performance of the ADWITT architecture substantially surpasses that of the conventional WITT (Wavelet Image Transmission Technique) model, particularly in scenarios characterized by harsh and detrimental channel conditions. These findings underscore the robustness and adaptability of the ADWITT approach, which is poised to improve the field of image transmission by offering superior performance and resilience in environments where traditional methods falter. [ABSTRACT FROM AUTHOR]

For high-quality picture transmission through smart devices in Mobile Multimedia Sensor Networks (MWMSN), high transmission rates, throughput, and a low Bit Error Rate are necessary. At the same time, energy efficiency is always a big problem for battery-powered smart devices like smartphones and tablets. MWMSN makes extensive use of cooperative communication to realize the benefits of the Multiple-Input-Multiple-Output technology. Energy consumption and routing are major challenges for Cooperative Mobile Multimedia Sensor Networks since each node in the network have mobility. The dynamic nature of MWSNs increases with mobility and the consequence is reflected in the control traffic overhead. To address these challenges, a Cluster-based Cooperative Multi-Hop Optimal Relay Selection (CCORS) strategy was proposed by using velocity, distance, and link quality parameters. The proposed technique determines the link quality for every pair of nodes based on values of signal strength and distance parameters. The relay nodes are chosen based on the highest possible Quality of Service (QoS) value, which is calculated to assure route stability, reliability, and durability. Further, we obtained an optimal number of cooperative nodes in every hop with the objective to minimize end-to-end energy consumption. Finally, simulation results demonstrate the effectiveness of the proposed algorithm compared to other state of art algorithms. [ABSTRACT FROM AUTHOR]

Image steganography is an extremely rich and significant exploration region that gives productive answers to some genuine and modern issues. This paper deals with secret image transmission and securing it from different attacks. The proposed image steganography technique uses a combination of image segmentation, pre-processing, and scrambling methos. The proposed technique begins with the segmentation of secret and cover images using Rubik's cube. The segmentation process breaks the images into six parts, then after they are stored in a segmented image dataset. In the second step, each segmented secret image is processed by the image pre-processing method. The proposed image pre-processing method helps the system select the appropriate cover image from the segmented cover image dataset, which makes the technique more robust. In the third step, before the embedding process, secret images are scrambled using the proposed scrambling method. Finally, the cover and secret images are processed by discrete wavelet transforms (DWT) and singular value decomposition (SVD) to generate the stego image. The proposed technique is tested on a variety of grayscale images, with peak signal-to-noise ratio (PSNR) values ranging from 32.27 to 30.77 (dB) and structural similarity index measure (SSIM) values ranging from 0.93 to 0.90 for different alpha values. The extracted secret image is analyzed using normalized correlation (NC) and naturalness image quality evaluator (NIQE) parameters. The NC values are above 0.99, and the NIQE values ranged from 3.3264 to 3.8468 for various extracted images. To analyze the proposed technique, measured value of entropy and an elapse time are 7.7956 and 6.489 s, respectively. Comparative studies are conducted in four main areas. The first comparative study tested the reliability of the proposed scrambling method by calculating the overall and diagonal correlation values of the secret image and scrambled secret image. The second comparative study tested the impeccability and reliability of the stego image by comparing its PSNR value to other stego images produced by other researchers. The third comparative study tested the effect of false-positive tests on extracted secret images. The results showed that the extracted secret image could only be obtained from the original stego image, indicating that the proposed method was secure against false positives. The fourth or last comparative study compares the computational load of proposed technique with previously developed techniques. In general, the results of the comparative study show that the proposed technique is reliable and secure for image scrambling, stego image generation, and secret image extraction. [ABSTRACT FROM AUTHOR]

Quantum image encryption is an innovative security method that exploits the principles of quantum physics to protect and transmit image data. By utilizing the unique properties of quantum mechanics such as superposition, non-cloning, and entanglement, this approach establishes a robust framework for safeguarding sensitive visual information. This review paper comprehensively examines the fundamental concepts of quantum image encryption and its significant impact on enhancing image transmission security. We explore how quantum technology has revolutionized security measures, offering novel solutions for the secure transmission of sensitive data, particularly images. Through rigorous analysis, we illuminate various methods of quantum encryption, including key generation, the confusion and diffusion principles, and the integration of artificial intelligence, especially optimization algorithms, in securing data. Furthermore, we discuss the challenges and future trends that researchers in this field may encounter. Our work provides valuable insights and guidance for those looking to build upon our research, contributing to a deeper understanding of quantum image encryption and laying the groundwork for further advancements in this area. [ABSTRACT FROM AUTHOR]

With the advancement of technology and the maturity of various aerial imaging techniques, data proprietors have awareness of the importance of secure protection for remote sensing images. In order to protect sensitive data of images, we propose a secure encoding scheme for compressing remote sensing images to decrease potential risks of data disclosure associated with such images. First, we designed the Sin chaos paradigm for constructing chaotic systems in various dimensions. As a result through relevant experiments, this chaos paradigm demonstrated effective scalability and stability. In addition, DNA transposition methods have been introduced to extend DNA encoding, expanding the range of DNA encoding from 1 to 4 and achieving dynamic selection of DNA transposition methods. This method reduces potential threats that conflict with fixed DNA encoding methods. In addition, in order to ensure the security of symmetric encryption and the efficiency of asymmetric encryption during key transmission, an elliptical curve "ring" key hiding strategy is adopted. Although the key embedding occupies 1.2% of the space in the ciphertext image, data redundancy realizes the implicit transmission of the key, improving the decryption efficiency of remote sensing images. In response to the above research, we propose a secure compression encoding scheme based on Sin chaotic paradigm and DNA transposition to ensure the security of remote sensing images. After cropping the original remote sensing image to a size of 1/16, the original image can still be decrypted. In addition, when the noise attack reaches 0.3, the ciphertext image can also be restored. Performance analysis and experimental data results show that our proposed secure compression encoding scheme has excellent robustness and security. [ABSTRACT FROM AUTHOR]

This paper proposes a highly secure image encryption technique based on chaotic synchronization. Firstly, through the design of a synchronization controller, we ensure that the master–slave chaotic extremum-coded random number generators (ECRNGs) embedded in separated transmitters and receivers are fully synchronized to provide synchronized dynamic random sequences for image encryption applications. Next, combining these synchronized chaotic sequences with the AES encryption algorithm, we propose an image segmentation and multi-encryption method to enhance the security of encrypted images and realize a secure image transmission system. Notably, in the design of the synchronization controller, the transient time before complete synchronization between the master and slave ECRNGs is effectively controlled by specifying the eigenvalues of the matrix in the synchronization error dynamics. Research results in this paper also show that complete synchronization of ECRNGs can be achieved within a single sampling time, which significantly contributes to the time efficiency of the image transmission system. As for the image encryption technique, we propose the method of image segmentation and use the synchronized dynamic random sequences generated by the ECRNGs to produce the keys and initialization vectors (IVs) required for AES-CBC image encryption, greatly enhancing the security of the encrypted images. To highlight the contribution of the proposed segmented image encryption, statistical analyses are conducted on the encrypted images, including histogram analysis (HA), information entropy (IE), correlation coefficient analysis (CCA), number of pixels change rate (NPCR), and unified average changing intensity (UACI), and compared with existing literature. The comparative results fully demonstrate that the proposed encryption method significantly enhances image encryption performance. Finally, under the network transmission control protocol (TCP), the synchronization of ECRNGs, dynamic keys, and IVs is implemented as well as segmented image encryption and transmission, and a highly secure image transmission system is realized to validate the practicality and feasibility of our design. [ABSTRACT FROM AUTHOR]

In response to the conflicting demands between real-time satellite communication and high-resolution synthetic aperture radar (SAR) imaging, we propose a method that aligns the data transmission rate with the imaging data volume. This approach balances SAR performance with the requirements for real-time data transmission. To meet the need for mobile user terminals to access real-time SAR imagery data of their surroundings without depending on large traditional ground data transmission stations, we developed an application system based on filter bank multicarrier offset quadrature amplitude modulation (FBMC-OQAM). To address the interference problem with SAR signals' transmission and reception, we developed a signal sequence based on spaceborne SAR echo and data transmission and reception. This system enables SAR and data transmission signals to share the same frequency band, radio frequency transmission system, and antenna, creating an integrated sensing and communication system. Simulation experiments showed that, compared to the equal power allocation scheme for subcarriers, the echo image signal-to-noise ratio (SNR) improved by 2.79 dB and the data transmission rate increased by 24.075 Mbps. [ABSTRACT FROM AUTHOR]

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In addition to susceptibility to performance degradation due to hardware malfunctions and environmental influences, wireless image transmission poses risks of information exposure to eavesdroppers. This paper delves into the image communications within wireless relay networks (WRNs) and proposes a secure cooperative relaying (SCR) protocol over Rayleigh fading channels. In this protocol, a source node (referred to as Alice) transmits superior-resolution (SR) images to a destination node (referred to as Bob) with the assistance of a mediating node (referred to as Relay) operating in decode-and-forward mode, all while contending with the presence of an eavesdropper (referred to as Eve). In order to conserve transmission bandwidth, Alice firstly reduces the size of the original SR images before transmitting them to Relay and Bob. Subsequently, random linear network coding (RLNC) is employed by both Alice and Relay on the downscaled poor-resolution (PR) images to obscure the original images from Eve, thereby bolstering the security of the image communications. Simulation results demonstrate that the proposed SCR protocol surpasses both secure relaying transmission without a direct link and secure direct transmission without relaying links. Additionally, a slight reduction in image quality can be achieved by increasing the scaling factor for saving transmission bandwidth. Furthermore, the results highlight the SCR protocol's superior effectiveness at Bob's end when compared to Eve's, which is due to Eve's lack of access to the RLNC coefficient matrices and reference images utilised by Alice and Relay in the RLNC process. Finally, the evaluation of reference images, relay allocations and diversity reception over Rayleigh fading channels confirms the effectiveness of the SCR protocol for secure image communications in the WRNs. [ABSTRACT FROM AUTHOR]

Currently, digital communication generates a considerable amount of data from digital images. Preserving the confidentiality of these images during transmission through network channels is of crucial importance. To ensure the security of this data, this article proposes an image encryption approach based on enhancing the Hill cipher by constructing pseudo-random matrices operating in the ring Z/212Z injected into a controlled affine transformation. This approach relies on the use of chaotic maps for generating matrices used in the encryption process. The use of the ring Z/212Z aims to expand the key space of our cryptosystem, thus providing increased protection against bruteforce attacks. Moreover, to enhance security against differential attacks, a matrix of size (4×4), not necessarily invertible, is also integrated into a diffusion phase. The effectiveness of our technique is evaluated through specific tests, such as key space analysis, histogram analysis, entropy calculation, negative pixel count rate (NPCR) and unified average changing intensity (UACI) values, correlation analysis, as well as avalanche effect assessment. [ABSTRACT FROM AUTHOR]

Traditional information hiding techniques achieve information hiding by modifying carrier data, which can easily leave detectable traces that may be detected by steganalysis tools. Especially in image transmission, both geometric and non-geometric attacks can cause subtle changes in the pixels of the image during transmission. To overcome these challenges, we propose a constructive robust image steganography technique based on style transformation. Unlike traditional steganography, our algorithm does not involve any direct modifications to the carrier data. In this study, we constructed a mapping dictionary by setting the correspondence between binary codes and image categories and then used the mapping dictionary to map secret information to secret images. Through image semantic segmentation and style transfer techniques, we combined the style of secret images with the content of public images to generate stego images. This type of stego image can resist interference during public channel transmission, ensuring the secure transmission of information. At the receiving end, we input the stego image into a trained secret image reconstruction network, which can effectively reconstruct the original secret image and further recover the secret information through a mapping dictionary to ensure the security, accuracy, and efficient decoding of the information. The experimental results show that this constructive information hiding method based on style transfer improves the security of information hiding, enhances the robustness of the algorithm to various attacks, and ensures information security. [ABSTRACT FROM AUTHOR]

A method of digital colorimetric determination of ammonium and nitrate in soils is proposed. The method is based on corresponding photometric procedures of ammonium and nitrate determination after potassium chloride extraction from soil samples. Ammonium is determined as an indophenol dye, and nitrate is determined as an azo dye. The original procedures were modified to overcome the lower sensitivity of the digital colorimetric method. For ammonium determination, the time required for the reaction to proceed completely was studied. Along with the use of a 96-well microplate protected from ambient light by a special frame, mathematical correction of scattered radiation using black ink and taking the images by a scanner in transmission mode without any post-processing, the resulting colorimetric methods proved to provide accuracy and sensitivity close to those of the spectrophotometric method, and the overall analysis speed for tens of samples was even higher. Limits of detection and quantitation for NO3– were 0.42 and 1.4 mg/kg, and for NH4+, they were 1.1 and 3.7 mg/kg, which is lower than for standard methods. The methods' validity was proven by the analysis of standard samples and by the analysis of soil samples collected in several districts of the Moscow region. [ABSTRACT FROM AUTHOR]

Electron energy-loss spectroscopy (EELS) can measure similar information to x-ray, UV–Vis, and IR spectroscopies but with atomic resolution and increased scattering cross-sections. Recent advances in electron monochromators have expanded EELS capabilities from chemical identification to the realms of synchrotron-level core-loss measurements and to low-loss, 10–100 meV excitations, such as phonons, excitons, and valence structures. EELS measurements are easily correlated with electron diffraction and atomic-scale real-space imaging in a transmission electron microscope (TEM) to provide detailed local pictures of quasiparticle and bonding states. This perspective provides an overview of existing high-resolution EELS (HR-EELS) capabilities while also motivating the powerful next step in the field—ultrafast EELS in a TEM. Ultrafast EELS aims to combine atomic-level, element-specific, and correlated temporal measurements to better understand spatially specific excited-state phenomena. Ultrafast EELS measurements also add to the abilities of steady-state HR-EELS by being able to image the electromagnetic field and use electrons to excite photon-forbidden and momentum-specific transitions. We discuss the technical challenges ultrafast HR-EELS currently faces, as well as how integration with in situ and cryo measurements could expand the technique to new systems of interest, especially molecular and biological samples. [ABSTRACT FROM AUTHOR]

Images and videos provide a wealth of information for people in production and life. Although most digital information is transmitted via optical fiber, the image acquisition and transmission processes still rely heavily on electronic circuits. The development of all-optical transmission networks and optical computing frameworks has pointed to the direction for the next generation of data transmission and information processing. Here, we propose a high-speed, low-cost, multiplexed parallel and one-piece all-fiber architecture for image acquisition, encoding, and transmission, called the Multicore Fiber Acquisition and Transmission Image System (MFAT). Based on different spatial and modal channels of the multicore fiber, fiber-coupled self-encoding, and digital aperture decoding technology, scenes can be observed directly from up to 1 km away. The expansion of capacity provides the possibility of parallel coded transmission of multimodal high-quality data. MFAT requires no additional signal transmitting and receiving equipment. The all-fiber processing saves the time traditionally spent on signal conversion and image pre-processing (compression, encoding, and modulation). Additionally, it provides an effective solution for 2D information acquisition and transmission tasks in extreme environments such as high temperatures and electromagnetic interference.

Sensor limitations in capturing devices and environmental factors can result in radiance artifacts in rendered images. This paper presents an entropy-driven exposure interpolation framework in the context of large exposure-ratio fusion. The proposed framework generates intermediate exposure-corrected images through transmission map estimation to obtain initial radiance and illumination maps. Fusion weight maps, within a pyramidal framework, are derived from the transmission map and spatial entropy, thereby enhancing the visual quality of images while preventing color artifacts. Experiments demonstrate that the proposed framework outperforms several state-of-the-art multi-exposure fusion schemes. [ABSTRACT FROM AUTHOR]

This paper presents an innovative approach for achieving rapid synchronization between two memristor chaotic circuits (MCCs), both with and without noise perturbations. The proposed adaptive control strategy effectively handles the uncertainty in control gains by adhering to predesigned update law. Additionally, this protocol is non-chattering and differentiable, avoiding the use of conventional discontinuous functions such as signum and absolute value functions. This method successfully mitigates the tremors caused by discontinuous functions. We derive two sufficient criteria using finite-time Lyapunov and stochastic finite-time Lyapunov stability methods. Numerical results validate the theoretical analysis and demonstrate the influence of noise intensity on convergence speed. Furthermore, the results have an application in image encryption transmission. [ABSTRACT FROM AUTHOR]

In the field of medical imaging, there is a strong requirement for the storage of an immense volume of digitized medical image data. The digital image must be compressed heavily before storing and transferring it because of having restricted bandwidth and scope of storage. When compression of images is done at a lower bit rate it reduces the image fidelity that results in a drop in quality but poses many challenges to overcome and prevents diagnostic miscalculations with great compression rates for reduced storage and quick transmission. To overcome this challenging issue several hybrid efficient compression procedures solely for medical digital images have been introduced in recent years. The transformation of image, quantization, and encoding is part of image compression. This paper presents a qualitative and comprehensive review of image compression techniques for two-dimensional (2D) still and three-dimensional (3D) medical images. The features and constraints associated with various compression methods for compressing grayscale images are reviewed and discussed in this paper. In-depth reviews of the practical concerns and difficulties in the medical scan compression arena are provided. [ABSTRACT FROM AUTHOR]

The image integrity of real-time monitoring is crucial for monitoring crop growth, helping farmers and researchers improve production efficiency and crop yields. Unfortunately, existing schemes just focus on ground equipment and drone imaging, neglecting satellite networks in remote or extreme environments. Given that satellite internet features wide area coverage, we propose SEAIS, a secure and efficient agricultural image storage scheme combining blockchain and satellite networks. SEAIS presents the mathematical model of image processing and transmission based on satellite networks. Moreover, to ensure the integrity and authenticity of image data during pre-processing such as denoising and enhancement, SEAIS includes a secure agricultural image storage and verification method based on blockchain, homomorphic encryption, and zero-knowledge proof. Specifically, images are stored via IPFS, with hash values and metadata recorded on the blockchain, ensuring immutability and transparency. The simulation results show that SEAIS exhibits more stable and efficient processing times in extreme environments. Also, it maintains low on-chain storage overhead, enhancing scalability. [ABSTRACT FROM AUTHOR]

Many fields, where human health and life are at risk, are increasingly utilizing mobile robots and UGVs (Unmanned Ground Vehicles). They typically operate in teleoperation mode (control based on the projected image, outside the operator's direct field of view), as autonomy is not yet sufficiently developed and key decisions should be made by the man. Fast and effective decision making requires a high level of situational and action awareness. It relies primarily on visualizing the robot's surroundings and end effectors using cameras and displays. This study aims to compare the effectiveness of three solutions of robot area imaging systems using the simultaneous transmission of images from three cameras while driving a UGV in complex terrain. [ABSTRACT FROM AUTHOR]

Digital image steganography serves as a technology facilitating covert communication through digital images by subtly incorporating secret data into a cover image. This practice poses a potential threat, as criminals exploit steganography to transmit illicit content, thereby jeopardizing information security. Consequently, it becomes imperative to implement defensive strategies against steganographic techniques. This paper proposes a novel defense mechanism termed "image vaccine" to safeguard digital images from steganography. The process of "vaccinating" an image renders it immune to steganographic manipulation. Notably, when criminals attempt to embed secret data into vaccinated images, the presence of such hidden information can be detected with a 100% probability, ensuring the consistent identification of stego images. This proactive approach enables the interception of stego image transmission, thereby neutralizing covert communication channels. [ABSTRACT FROM AUTHOR]

The segmentation and extraction of oilseed rape crop rows are crucial steps in visual navigation line extraction. Agricultural autonomous navigation robots face challenges in path recognition in field environments due to factors such as complex crop backgrounds and varying light intensities, resulting in poor segmentation and slow detection of navigation lines in oilseed rape crops. Therefore, this paper proposes VC-UNet, a lightweight semantic segmentation model that enhances the U-Net model. Specifically, VGG16 replaces the original backbone feature extraction network of U-Net, Convolutional Block Attention Module (CBAM) are integrated at the upsampling stage to enhance focus on segmentation targets. Furthermore, channel pruning of network convolution layers is employed to optimize and accelerate the model. The crop row trapezoidal ROI regions are delineated using end-to-end vertical projection methods with serialized region thresholds. Then, the centerline of oilseed rape crop rows is fitted using the least squares method. Experimental results demonstrate an average accuracy of 94.11% for the model and an image processing speed of 24.47 fps/s. After transfer learning for soybean and maize crop rows, the average accuracy reaches 91.57%, indicating strong model robustness. The average yaw angle deviation of navigation line extraction is 3.76°, with a pixel average offset of 6.13 pixels. Single image transmission time is 0.009 s, ensuring real-time detection of navigation lines. This study provides upper-level technical support for the deployment of agricultural robots in field trials. [ABSTRACT FROM AUTHOR]

Objective: Nowadays, the prevalence of cognitive impairment in women has gradually increased, especially in postmenopausal women. There were few studies on the mechanistic effects of iron exposure on neurotoxicity in postmenopausal women. The aim of this study is to investigate the effect of iron accumulation on cognitive ability in ovariectomized mice and its possible mechanism and to provide a scientific basis for the prevention of cognitive dysfunction in postmenopausal women. Methods: Female C57BL/6N ovariectomized model mice were induced with ferric citrate (FAC). The mice were randomly divided into 5 groups: control, sham, ovariectomized (Ovx), Ovx + 50 mg/kg FAC (Ovx + l), and Ovx + 100 mg/kg FAC (Ovx + h). The impact of motor and cognitive function was verified by a series of behavioral tests. The levels of serum iron parameters, malondialdehyde, and superoxide dismutase were measured. The ultrastructure of mice hippocampal microglia was imaged by transmission electron microscopy. The differential expression of hippocampal proteins was analyzed by Tandem Mass Tag labeling. Results: Movement and cognitive function in Ovx + l/Ovx + h mice were significantly decreased compared to control and Sham mice. Then, iron exposure caused histopathological changes in the hippocampus of mice. In addition, proteomic analysis revealed that 29/27/41 proteins were differentially expressed in the hippocampus when compared by Ovx vs. Sham, Ovx + l vs. Ovx, as well as Ovx + h vs. Ovx + l groups, respectively. Moreover, transferrin receptor protein (TFR1) and divalent metal transporter 1 (DMT1) protein expression were significantly increased in the iron accumulation mice model with ovariectomy. Conclusion: Iron exposure could cause histopathological damage in the hippocampus of ovariectomised mice and, by altering hippocampal proteomics, particularly the expression of hippocampal iron metabolism‐related proteins, could further influence cognitive impairment in ovariectomized mice. [ABSTRACT FROM AUTHOR]

Purpose: To use X-ray computed tomography (CT) --which describes the acquisition and reconstruction of 2-dimensional X-ray transmission images to create a 3D representation of a specimen --in the analyses of intraocular lenses (IOLs) explanted because of optical opacification occurring postoperatively. Setting: John A. Moran Eye Center, and Utah Nanofab, University of Utah, Salt Lake City, Utah. Design: Laboratory study. Methods: A hydrophilic acrylic and a silicone lens (the latter from an eye with asteroid hyalosis) explanted because of postoperative calcification, as well as a poly(methyl methacrylate) (PMMA) lens explanted because of snowflake degeneration underwent analysis under gross and light microscopy. Then, they were attached to an appropriate support and scanned under a Zeiss Xradia Versa X-ray microscope. After data acquisition, data segmentationwas performed with a commercially available program to separate image data into components. Results: Morphology, size/volume, and specific location of calcified deposits on the surface or within the substance of explanted IOLs could be demonstrated by X-ray CT within the entire volume of each lens with high contrast and resolution. The PMMA lens showed multiple spaces/fissures in relation to Nd:YAG pitting of the optic, and what appeared to be sheets of delaminated PMMA material at different levels within the optic substance. Conclusions: The key benefit of X-ray CT is that it can be performed without physically sectioning the specimen. This preliminary study demonstrates that this technology can be potentially useful in the imaging and analyses of explanted, opacified lenses. [ABSTRACT FROM AUTHOR]

This study reported the synthesis of well-dispersed palladium nanoparticles (PdNPs) using microwaves. Additionally, this method is quick, cheap, chemical-free, and environmentally friendly. The Eupatorium adenophorum aqueous extract, which contains polysaccharides and other phytochemicals, effectively reduced and stabilized PdNPs. We have preliminarily confirmed that PdNPs form via UV–visible spectroscopy and proposed a mechanism of PdNPs formation via Fourier transform infrared spectroscopy. EA-PdNPs have a face-centred cubic structure, as confirmed by XRD analysis. The images obtained by transmission electron microscopy showed spherical PdNPs whose average size was 11 ± 2 nm. EA-PdNPs showed good catalytic activity towards the reduction of methylene blue (MB), congo red (CR) dyes, and 4-nitrophenol (4-NP). It was found that EA-PdNPs showed a reduction efficiency of 94% against MB, CR, and 4-NP dyes even after five cycles. EA-PdNPs are anticipated to contribute to environmental water remediation significantly. Schematic representation of the synthesis of EA-PdNPs and their catalytic applications [ABSTRACT FROM AUTHOR]

This paper proposes an asymmetric scanning holography cryptosystem based on the Elgamal algorithm. The method encodes images with sine and cosine holograms. Subsequently, each hologram is divided into a signed bit matrix and an unsigned hologram matrix, both encrypted using the sender's private key and the receiver's public key. The resulting ciphertext matrices are then transmitted to the receiver. Upon receipt, the receiver decrypts the ciphertext matrices using their private key and the sender's public key. We employ an asymmetric single-image encryption method for key management and dispatch for securing imaging and transmission. Furthermore, we conducted a sensitivity analysis of the encryption system. The image encryption metrics, including histograms of holograms, adjacent pixel correlation, image correlation, the peak signal-to-noise ratio, and the structural similarity index, were also examined. The results demonstrate the security and stability of the proposed method. [ABSTRACT FROM AUTHOR]

Balancing security with image quality is a critical challenge in image encryption, particularly for applications like medical imaging that require high visual fidelity. Traditional encryption methods often fail to preserve image integrity and are vulnerable to advanced attacks. This paper introduces CryptoGAN, a novel GAN-based model designed for image encryption. CryptoGAN employs an architecture to effectively encrypt a dataset of 2000 butterfly images with a resolution of 256x256 pixels, integrating Generative Adversarial Networks (GANs) with symmetric key encryption. Using a U-Net Generator and a PatchGAN Discriminator, CryptoGAN optimizes for key metrics including Structural Similarity Index (SSIM), entropy, and correlation measures. CryptoGAN's performance is comprehensively compared against state-of-theart models such as Cycle GAN-based Image Steganography, EncryptGAN, and DeepEDN. Our evaluation, based on metrics like SSIM, entropy, and PSNR, demonstrates CryptoGAN's superior ability to enhance encryption robustness while maintaining high image quality. Extensive experimental results confirm that CryptoGAN effectively balances security and visual fidelity, making it a promising solution for secure image transmission and storage. This study is supported by a literature survey and detailed analysis of the model architecture, underscoring CryptoGAN's significant contributions to the field of image encryption. [ABSTRACT FROM AUTHOR]

The current manual inspection of transmission line images captured by unmanned aerial vehicles (UAVs) is not only time-consuming and labor-intensive but also prone to high rates of false detections and missed inspections. With the development of artificial intelligence, deep learning-based image recognition methods can automatically detect various defect categories of transmission lines based on images captured by UAVs. However, existing methods are often constrained by incomplete feature extraction and imbalanced sample categories, which limit the precision of detection. To address these issues, a novel method based on multi-strategy image processing and an improved deep network is proposed to conduct defect diagnosis of transmission lines. Firstly, multi-strategy image processing is proposed to extract the effective area of transmission lines. Then, a generative adversarial network is employed to generate images of transmission lines to enhance the trained samples' diversity. Finally, the deep network GoogLeNet is improved by superseding the original cross-entropy loss function with a focal loss function to achieve the deep feature extraction of images and defect diagnosis of transmission lines. An actual imbalance transmission line dataset including normal, broken strands, and loose strands is applied to validate the effectiveness of the proposed method. The experimental results, as well as contrastive analysis, reveal that the proposed method is suitable for recognizing defects of transmission lines. [ABSTRACT FROM AUTHOR]

With the advent of quantum computing, traditional cryptography algorithms are at risk of being broken. Post-quantum encryption algorithms, developed to include mathematical challenges to make it impossible for quantum computers to solve problems, are constantly being updated to ensure that sensitive information is protected from potential threats. In this study, a hybrid examination of a (p,q)-Bernstein-type polynomial, which is an argument that can be used for encryption algorithms with a post-quantum approach, was made from a mathematical and cryptography perspective. In addition, we have aimed to present a new useful operator that approximates functions and can be used in cases where it is not possible to work with functions in the fields of technology, medicine, and engineering. Based on this idea, a new version of the (p,q)-Bernstein-Schurer operator was introduced in our study on a variable interval and the convergence rate was calculated with two different methods. At the same time, the applications of the theoretical situation in the study were presented with the help of visual illustrations and tables related to the approach. Additionally, our operator satisfied the statistical-type Korovkin theorem and is suitable for variable interval approximation. This is the first paper to study the statistical convergence properties of (p,q)-Bernstein-Schurer operators defined on a variable bounded interval, to obtain special matrices with the help of (p,q)-basis functions, and to give an application of (p,q)-type operators for encrypted image transmission. [ABSTRACT FROM AUTHOR]

We establish a sample‐ and data‐processing pipeline that allows for high‐throughput optical microscope measurement of porous films, provided they are sufficiently optically scattering. Here, self‐limiting electrospray deposition (SLED) is used to manufacture scattering films of different morphologies. This technique compensates for the scattering of the films through background subtraction of the reflection image with the transmission image. This process is implemented through a combination of an ImageJ and MATLAB data pipeline; the Canny edge‐detector is used as the image‐processing algorithm to identify the boundaries of the film. This process is verified against manually measured images; a comparative study between cross‐sectional scanning electron microscopy (where scattering effects are diminished) and optical microscopy also verifies that our optical microscopy technique can be used to consistently, non‐destructively measure film thickness regardless of film morphology. In addition, this technique can be used in combination with dense film measurements to measure film porosity. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "AAA237, an SKP2 inhibitor, suppresses glioblastoma by inducing BNIP3-dependent autophagy through the mTOR pathway" published in Cancer Cell International. The correction addresses the incorrect figures that appeared in the original article and provides the corrected figures. The corrected figures include graphs showing the effects of AAA237 on the viability, proliferation, and autophagy of glioblastoma cells. The correction also includes Western blot analysis results and other experimental data. The correction notice is authored by Yizhi Zhang, Wan Li, Yihui Yang, Sen Zhang, Hong Yang, Yue Hao, Xu Fang, Guanhua Du, Jianyou Shi, Lianqiu Wu, and Jinhua Wang. [Extracted from the article]

Image encryption is one of the most widely used techniques for securing images in trusted and unrestricted public media. However, the drawback is weak security in chaotic encryption algorithms, small key space and hardware implementation complexities. Various appropriate encryption algorithms have been carried out for secure image transmission; it becomes a critical issue to protect image integrity, confidentiality and authenticity. To overcome these issues, this article examines several existing memristor-based image encryption algorithms with various chaotic maps. As a result, this research aims to deliver comprehensive literature on image encryption techniques through memristor to help the researchers. Finally, this survey provides all vital literature on the current image encryption techniques with their benefits, drawbacks, developments, and future directions. We also give a general guideline about cryptography. We conclude that all methods are helpful for real-time image encryption. A comparison has been made between many image processing approaches (conventional and memristor) based on metrics such as the number of pixels change rate (NPCR) with the value of 0.9986, histogram, entropy (7.9993), unified average varying intensity (UACI) achieves the value as 0.4996, energy consumption as 0.32pJ and time complexity as 0.9s. The experimental results of various approaches, key sensitivity and statistical analysis revealed that the survey of memristor-based image encryption schemes provides an effective way to secure image transmission in real-time application. [ABSTRACT FROM AUTHOR]

To ensure the secure and efficient transmission of images, we propose a new image encryption algorithm based on a chaotic system with free control and zigzag scrambling. The performance of the chaotic system is analyzed using the phase trajectory, Lyapunov exponents (LEs), and bifurcation diagram, which demonstrate its good ergodicity, complex chaotic behavior, large and continuous chaotic range, and stable Lyapunov exponent spectrum. In addition, based on this chaotic system, this algorithm also provided the security for the protection of image data. The algorithm involves scrambling pixel positions using an improved zigzag algorithm and substituting pixel values. The simulation and analysis results show that the proposed algorithm has high security and low time complexity. It can resist various attacks, including statistical analysis, differential attacks, brute-force attacks, known plaintext attacks, and chosen plaintext attacks. The experimental simulations and its performance tests prove that the proposed scheme is effective and secure in image data. [ABSTRACT FROM AUTHOR]

The present study deals with image enhancement, which is a very common problem in image processing. This issue has been addressed in multiple works with different methods, most with the sole purpose of improving the perceived quality. Our goal is to propose an approach with a strong physical justification that can model the human visual system. This is why the Logarithmic Image Processing (LIP) framework was chosen. Within this model, initially dedicated to images acquired in transmission, it is possible to introduce the novel concept of negative grey levels, interpreted as light intensifiers. Such an approach permits the extension of the dynamic range of a low-light image to the full grey scale in "real-time", which means at camera speed. In addition, this method is easily generalizable to colour images and is reversible, i.e., bijective in the mathematical sense, and can be applied to images acquired in reflection thanks to the consistency of the LIP framework with human vision. Various application examples are presented, as well as prospects for extending this work. [ABSTRACT FROM AUTHOR]

The introduction of quantum communications, enabled by advancements in quantum computing, is expected to play a significant role in the field of communications. Inherent properties of quantum objects, such as superposition and entanglement, have the potential to provide novel solutions to overcome the challenges encountered by classical communication systems in bandwidth‐intensive applications such as media transmission. This research explores the performance of a quantum communication system in image transmission using quantum superposition and investigates its performance using a simple quantum channel model. With an increase in channel noise, there are significant gains in the rate distortion performance of images transmitted over the quantum channel compared to an ideal classical channel. This novel attempt at constructing a quantum communication‐based image transmission system indicates the potential of the approach to be applied to satisfy the ever‐increasing demands of high‐quality media transmission applications. [ABSTRACT FROM AUTHOR]

Image defogging is an essential technology used in traffic safety monitoring, military surveillance, satellite and remote sensing image processing, medical image diagnostics, and other applications. Current methods often rely on various priors, with the dark-channel prior being the most frequently employed. However, halo and bright-field color distortion issues persist. To further improve image quality, an adaptive image-defogging algorithm based on bright-field region detection is proposed in this paper. Modifying the dark-channel image improves the abrupt changes in gray value in the traditional dark-channel image. By setting the first and second lower limits of transmittance and introducing an adaptive correction factor to adjust the transmittance of the bright-field region, the limitations of the dark-channel prior in extensive ranges and high-brightness areas can be significantly alleviated. In addition, a guide filter is utilized to enhance the initial transmittance image, preserving the details of the defogged image. The results of the experiment demonstrate that the algorithm presented in this paper effectively addresses the mentioned issues and has shown outstanding performance in both objective evaluation and subjective visual effects. [ABSTRACT FROM AUTHOR]

This study introduces an innovative enhancement to the U-Net architecture, termed Modified DRU-Net, aiming to improve the segmentation of cell images in Transmission Electron Microscopy (TEM). Traditional U-Net models, while effective, often struggle to capture fine-grained details and preserve contextual information critical for accurate biomedical image segmentation. To overcome these challenges, Modified DRU-Net integrates dense residual connections and attention mechanisms into the U-Net framework. Dense connections enhance gradient flow and feature reuse, while residual connections mitigate the vanishing gradient problem, facilitating better model training. Attention blocks in the up-sampling path selectively focus on relevant features, boosting segmentation accuracy. Additionally, a combined loss function, merging focal loss and dice loss, addresses class imbalance and improves segmentation performance. Experimental results demonstrate that Modified DRU-Net significantly enhances performance metrics, underscoring its effectiveness in achieving detailed and accurate cell image segmentation in TEM images. [ABSTRACT FROM AUTHOR]

The high information rates and energy necessities for picture transmission overLow-Power Wide Area Network (LPWAN) protocols have for some time been an issue. One such protocol is vast Range (LoRa), which has created extreme worries over its appropriateness for picture transmission because of its low information rate, yet being powerful for sending information over tremendous distances. This study presents the application results of a coordinated LoRa and Deep Learning-based PC vision framework that can precisely recognize diseases of grape leaves from low-goal pictures. In particular, this work centers around coordinating the two advances -- LoRa and deep Learning -- to work with the transmission of pictures and the recognition of sicknesses. The framework utilizes a blend of recreation and on location tests, different LoRa settings, and tweaking the CNN model to accomplish this point. The assessment demonstrated the way that the proposed system could send pictures over LoRa while sticking to convention constraints (such low obligation cycle and data transmission). Sicknesses of grape leaves might be dependably distinguished by our superior model. The strategy requires no preparation information to change boundaries, and it is both successful and adaptable enough to oblige the unmistakable elements of each and every leaf sickness. It is vital to take note of that end-client trust in machine and deep learning models has fundamentally expanded because of novel arrangements in the Explainable Artificial Intelligence (XAI) space. In this work, we utilize the Graduate CAM technique to show the result layer choices made by the CNN. The perception discoveries show that there is a significant feeling of the sickness' spot area. The organization recognizes a few grape leaf illnesses along these lines. [ABSTRACT FROM AUTHOR]

Featured Application: The future applications of the present study are to secure patient information and diagnostic details within medical images, ensuring data integrity and authenticity. The method enhances the security of medical records during storage, transmission, and especially in telemedicine, where images are frequently shared over digital networks. The growing adoption of telemedicine necessitates robust security measures for medical images during transmission. This paper proposes a novel blind watermarking system for medical images that utilizes both image gradients and the Discrete Wavelet Transform (DWT). Image gradients, acting as spatial derivatives, provide a "topological map" of the image, aiding in the identification of areas susceptible to disruption. The DWT, with its multi-resolution analysis, offers a favorable balance between robustness and imperceptibility. The proposed method embeds the watermark within the low–low band (LL) of the DWT-decomposed image, specifically in 3 × 3 block regions selected based on gradient information. The mathematical relationships between the gradient's direction and magnitude are employed to extract the corresponding blocks and their codes adequately. These codes are then XORed with the watermark and embedded into the chosen blocks using the least significant bit (LSB) technique. Extensive experimentation on a medical image dataset evaluates the system's performance against some attacks like filtering, noise, and scaling. The results demonstrate the efficacy of the proposed approach in hiding information while ensuring the security and integrity of watermarked medical images. [ABSTRACT FROM AUTHOR]

Imaging with undetected photons relies upon nonlinear interferometry to extract the spatial image from an infrared probe beam and reveal it in the interference pattern of an easier-to-detect visible beam. Typically, the transmission and phase images are extracted using phase-shifting techniques and combining interferograms from multiple frames. Here we show that off-axis digital holography enables reconstruction of both transmission and phase images at the infrared wavelength from a single interferogram, and hence a single frame, recorded in the visible. This eliminates the need for phase stepping and multiple acquisitions, thereby greatly reducing total measurement time for imaging with long acquisition times at low flux or enabling video-rate imaging at higher flux. With this single-frame acquisition technique, we are able to reconstruct transmission images of an object in the infrared beam with a signal-to-noise ratio of 3.680 ± 0.004 at 10 frames per second, and record a dynamic scene in the infrared beam at 33 frames per second. [ABSTRACT FROM AUTHOR]

There are numerous applications of terahertz (THz) imaging in many fields. However, current THz imaging is generally based on scanning technique due to the limited intensity of the THz sources. Thus, it takes a long time to obtain a frame image of the target and cannot meet the requirement of fast THz imaging. Here, we demonstrate a single-shot direct THz imaging strategy based on a broadband intense THz source with a frequency range of 0.1~23 THz and a THz camera with a frequency response range of 1~7 THz. This THz source was generated from the laser–plasma interaction, with its central frequency at ~12 THz. The frame rate of this imaging system was 8.5 frames per second. The imaging resolution reached 146.2 μm. With this imaging system, a single-shot THz image for a target object with a size of more than 7 cm was routinely obtained, showing a potential application for fast THz imaging. Furthermore, we proposed and tested an image enhancement algorithm based on an improved dark channel prior (DCP) theory and multi-scale retinex (MSR) theory to optimize the image brightness, contrast, entropy and peak signal-to-noise ratio (PSNR). [ABSTRACT FROM AUTHOR]

Thallium (Tl) and its two cationic species, Tl(I) and Tl(III), are toxic for most living beings. In this work, we investigated the effects of Tl (10–100 µM) on the viability and proliferation capacity of the adherent variant of PC12 cells (PC12 Adh cells). While both Tl(I) and Tl(III) halted cell proliferation from 24 h of incubation, their viability was ~ 90% even after 72 h of treatment. At 24 h, increased levels of γH2AX indicated the presence of DNA double-strand breaks. Simultaneously, increased expression of p53 and its phosphorylation at Ser15 were observed, which were associated with decreased levels of p-AKTSer473 and p-mTORSer2448. At 72 h, the presence of large cytoplasmic vacuoles together with increased autophagy predictor values suggested that Tl may induce autophagy in these cells. This hypothesis was corroborated by images obtained by transmission electron microscopy (TEM) and from the decreased expression at 72 h of incubation of SQSTM-1 and increased LC3β-II to LC3β-I ratio. TEM images also showed enlarged ER that, together with the increased expression of IRE1-α from 48 h of incubation, indicated that Tl-induced ER stress preceded autophagy. The inhibition of autophagy flux with chloroquine increased cell mortality, suggesting that autophagy played a cytoprotective role in Tl toxicity in these cells. Together, results indicate that Tl(I) or Tl(III) are genotoxic to PC12 Adh cells which respond to the cations inducing ER stress and cytoprotective autophagy. [ABSTRACT FROM AUTHOR]

The multispectral satellite sensor images have multibands, which have some typical noise. There is difficult to detect this tipical noise with low resolution image. The satellite local or gloval pixel information and quantificationare degraded due to this noise. Many standard transformations and filtering operations are developed for detection and removing of non-gaussion noise, which are not given sophisticated results with existing methods. These statistical characteristics are applied to those samples to identify and quantify present tipical noise. The higher-order statistical based machine learning algorithm is developing to remove the speckle noise from satellite image. In this proposed algorithm, implemented the higher order statistical approache such as skewness, kurtosis based adaptive curvelet methods are implemented for the detection and suppression of speckle noise with retrieve of spectral and spectral values. The proposed algorithm preserves smooth and sharp details and maintains the tradeoff level in multispectral bands is suitable for advanced high speed 5G communication with the effective rate of transmission. The proposed results are verified with suitable statistical parameters such as PSNR, Entropy and ERGAS values. [ABSTRACT FROM AUTHOR]

Underwater optics have seen a notable surge of interest in recent years, emerging as a critical medium for conveying information crucial to underwater resource exploration, autonomous underwater vehicle navigation, etc. The intricate dynamics of underwater optical transmission, influenced by factors such as the absorption by the water and scattering by multiple particles, present considerable challenges. One of the most critical issues is that the optical information representation methods fail to take into account the impact of the underwater physical environment. We conducted a comprehensive review and analysis of recent advancements in underwater optical transmission laws and models. We summarized and analyzed relevant research on the effects of underwater particles and turbulence on light and analyzed the polarization effects in various environments. Then, the roles of various types of underwater optical propagation models were analyzed. Although optical models in complex environments are still mostly based on Monte Carlo methods, many underwater optical propagation mechanisms have been revealed and can promote the impacts of optical information expression. We delved into the cutting-edge research findings across three key domains: the enhancement of underwater optical image quality, the 3D reconstruction from monocular images, and the underwater wireless optical communication, examining the pivotal role played by light transmission laws and models in these areas. Drawing upon our extensive experience in underwater optics, including underwater optical sensor development and experiments, we identified and underscored future directions in this field. We advocate for the necessity of further advancements in the comprehension of underwater optical laws and physical models, emphasizing the importance of their expanded application in underwater optical information representations. Deeper exploration into these areas is not only warranted but essential for pushing the boundaries of current underwater optical technologies and unlocking new potential for their application in underwater optical sensor developments, underwater exploration, environmental monitoring, and beyond. [ABSTRACT FROM AUTHOR]