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With the advancement of quantum image research, the security of quantum images has also become the focus. The mutimode quantum image representation based on three dimensional coordinates (TMQIR) is efficient and general. Based on the least significant bit (LSB), a blind watermarking scheme for TMQIR images is proposed in this paper. For color images, a RGB carrier TMQIR image is transformed to grayscale based on any two of three color weights. And any two weights can be used as the key to the conversion between color image and grayscale image. Then the grayscale image with watermark is converted into color image according to the selected color weights. In the LSB of the grayscale TMQIR image used as carrier image and watermarked image, the binary watermark image can be embedded and extracted respectively. In the extracting process, a series of operations are performed in the reverse order of the watermarking process. In addition, the quantum circuits in the watermarking and extracting process of the proposed blind watermarking scheme are simulated on IBM Quantum Lab platform. The simulation results show that the scheme is correct and effective, and the scheme is better than the previous schemes in complexity and key space. [ABSTRACT FROM AUTHOR]

This article argues that there are parallels between developments in modern science and in art and culture, including the culture of finance, and that these developments can be tracked by a notion of volatility not just as change, but as how change itself has changed. Describing this paradigm shift requires a language that is precise but indeterminate, a language akin to metaphor, understood as figures of volatility. Three such figures are anamorphosis, anachronism, and catachresis. These figures are major instantiations of volatility, though they do not exhaust all the possibilities. What they indicate is not just that our frames of understanding have shifted, but that we are dealing with problematic, multiple, and overlapping frames: anamorphosis problematizes our experience of space, anachronism of time, and catachresis of language. These figures are not all in play at the same time. In literature, catachresis may be the dominant figure; in dance, anamorphosis; in ‘slow cinema’, anachronism. The aim is less to arrive at a set of defining characteristics than to follow a series of transformations across different cultural fields. Almost every field in our time is volatile each in its own way, and this has consequences for methodology. If figures are tools to think with, not to regulate thought, a necessary method would be to allow these figures to emerge from the material, not from a checklist. The question of volatility is arguably the key intellectual challenge of our time because it allows us to see deviation from a norm not just as an aberration, but as an indication that established norms are losing their normative value.

This paper proposes a new algorithm for binarizing the grayscale quantum images represented by novel enhanced quantum image representation(NEQR) through pixel qubit flipping. The algorithm consists of two steps: the first step performs the qubit state checking, and the second completes pixel qubit flipping based on the results in previous step. The key data analysis shows that our algorithm has the following advantages, which include: (1) Contrasting with the probable algorithm, the result of this paper is deterministic( without error). (2) Comparing with the latest result, our paper has some superior characters: fewer quantum gates, fewer auxiliary qubits and less quantum delay.

This paper proposes a novel quantum color image steganography algorithm using an efficient embedding technique of exploiting modification direction (EMD). In this paper, the EMD algorithm is improved to reduce the number of modified pixels and smooth the noticeable changes at both ends of the histogram of hidden images. Besides, a fractional-order chaotic system is proposed to increase the security of secret information. The effective quantum circuit for the quantum steganography algorithm is also presented in this paper. The simulation and numerical analysis demonstrate that the proposed algorithm has good performance in imperceptibility analysis, capacity analysis and security analysis. [ABSTRACT FROM AUTHOR]

There are three distinct types of quantum image representations: amplitude-based states, phase-based states, and index-based states. All of these states are proposed in relation to the various physical information carriers and have been extensively used in previous research. However, the correlations hidden in these states are not analyzed, nor is the optimal state for image representation determined. A new assessment standard, namely description ability, is proposed to address this issue. The relationships between description abilities and these states are discussed in terms of this criterion under the multiple correlated conditions of state preparations, state transforms, and coloring abilities. The objective of differentiating and determining which state is the optimal choice for the state representation of quantum images could be accomplished using these numerical relations. [ABSTRACT FROM AUTHOR]

The digital image representation model directly affects the performance of digital image processing based on the representation model. Most quantum image representations which are based on traditional digital images, require a large number of qubits, or the complicated and difficult operations of quantum image processing. In this paper, we record the value and position of each bit in the binary sequence to form a multimode quantum image representation (MQIR) based on three-dimensional coordinates, which effectively reduces the number of qubits required to store the image. However, the basic operations for traditional digital images (such as scale operations) cannot be applied to MQIR image. To solve this problem, this paper proposes the nearest-neighbor interpolation scaling schemes for MQIR image, then we design and implement the quantum image scaling circuits. Finally, the complexity analysis and experimental simulation results of the scaling circuits for MQIR image are given. The simulation results verify the correctness of the image scaling schemes and circuits for MQIR image. [ABSTRACT FROM AUTHOR]

Land use/Land cover (LULC) plays a vital role in planning and supervising the utilization of the natural resources based on the gradual increase in the human demands in the current ecosystem. This study mainly focuses on the usage of the geographic information system (GIS) and land usage to identify the changes in Ananthapuramu, which is located in the Ananthapur district of Andhra Pradesh (AP) state, South India. This paper mainly focuses on the classification and identification of the changes in LULC in the period of 1999–2019 based on a survey of India’s topographic map and temporal images gathered from the satellite. The experimental results indicate that over the specified period of study, the rate of increment and decrement in the built-up area, rate of underwater bodies, forest bodies that may demonstrate a significant impact on the environmental ecosystem.

The image is one of the most important means to store information, and is widely used in every aspect of life. However, the characteristics of images enable them to be easily stolen, tampered with, and copied. Researchers have proposed many encryption methods, with most applying only to traditional digital images. There are few encryption methods for quantum images, and quantum image-oriented encryption technology has begun to attract researchers' attention. This study proposes a quantum image encryption method based on DNA Controlled-Not (DNACNot). Based on the quantum image information, encryption parameters are obtained and transferred as part of a chaotic initial key. Two natural DNA sequences are amplified to obtain the DNA coordinate sequence, and a modified chaos game representation is used to modify the DNA coordinate sequence, which is then used to correct the sequence generated by chaos. The resulting sequence is converted to an integer sequence to obtain DNACNot. A controlled-not operation is performed between DNACNot and the quantum image is scrambled by bit-plane to obtain the encrypted image. The encryption method has high security, a good encryption effect, and a large key space. The method can effectively resist exhaustive, statistical, and differential attacks. The algorithm is easy to implement at a low cost. The encryption time of our proposed method is satisfactory, and the method is suitable for real-time encryption. Moreover, the encryption results can be transmitted over the internet and stored in the cloud.

Quantum image processing, which merges classical image processing techniques with quantum computing, provides exceptional storage capacity and unparalleled parallel computing power. In this study, we present a quantum color image watermarking scheme that employs quantum error correction codes to address issues such as pixel loss and image distortion during watermark embedding and extraction. By utilizing the least significant bit method to embed the color values of the watermark image into those of the carrier image, we improve the scheme’s robustness. We also address the error correction capabilities of channel coding for phase-flip errors and follow the majority principle, resulting in more accurate extraction of the watermark image’s color and enhancing the watermarking scheme’s reliability and integrity. Our experimental simulations demonstrate that the proposed watermarking scheme boasts high security, strong robustness, and excellent concealment.

Copyright of Journal of Computer-Aided Design & Computer Graphics / Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Land use/Land cover (LULC) plays a vital role in planning and supervising the utilization of the natural resources based on the gradual increase in the human demands in the current ecosystem. This study mainly focuses on the usage of the geographic information system (GIS) and land usage to identify the changes in Ananthapuramu, which is located in the Ananthapur district of Andhra Pradesh (AP) state, South India. This paper mainly focuses on the classification and identification of the changes in LULC in the period of 1999–2019 based on a survey of India's topographic map and temporal images gathered from the satellite. The experimental results indicate that over the specified period of study, the rate of increment and decrement in the built-up area, rate of underwater bodies, forest bodies that may demonstrate a significant impact on the environmental ecosystem. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhengzhou University (Natural Science Edition) is the property of Journal of Zhengzhou University (Natural Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

At present, quantum image data hiding technology is restricted by high fidelity and embedding capacity, which frequently leads to permanent distortion of carrier images. A reversible data hiding method based on quantum controlled- NOT (CNOT) gate operation was proposed in the present study to satisfy the requirements of embedding capacity and visual quality and recover the original carrier image without loss. First, the hidden and carrier images were represented by a novel enhanced quantum representation of digital images. The hidden images were then encrypted and scrambled by employing chaos method. The quantum secret image was embedded into the relevant bit plane of the quantum carrier image considering quantum CNOT gate operation. The quantum key image was also generated. Finally, the current work not only extracted the quantum secret image without error but also recovered the carrier image without loss via inverse quantum CNOT gate operation. Simulation experiments were conducted to analyze embedding concealment and visual quality of the embedded steganographic images. Results demonstrate that the quantum circuit based on quantum CNOT gate operation not only enhances the embedding concealment but also improves the peak signal-to-noise ratio at the embedding capacity of 2 bits per pixel by 10% compared with the traditional least significant bit method. Thus, this operation achieves the lossless recovery of the original quantum carrier image. This study also provides certain theoretical importance and practical value for the security authentication and protection of quantum images. [ABSTRACT FROM AUTHOR]

Inspired on the classical Bayesian method also called mutual information, by generalizing the classical case to quantum approach to study the multipartite correlation in quantum image by using the flexible representation of quantum images (FRQI) method. Some important entanglement measures are calculated including von Neumann entropy, conditional entropy, joint entropy, discord and mutual information. We take two typical images of size 2 × 2 pixels and 8 × 8 pixels and study their entanglement measures from different classical and quantum point of view. The quantum image of size 2 × 2 is studied under the change of color for one pixel, but the quantum image of 8 × 8 is treated under translation transform. We find that the classical joint entropy remains invariant under the change of color for one pixel but the quantum entropy is sensitive to such change. It is shown that the total correlation IT could arrive to the double amount of the classical joint entropy. The discord in the classical case is zero, but it varies much in the quantum case. [ABSTRACT FROM AUTHOR]

This paper is concerned with the better security of quantum image secret sharing (QISS) algorithm. The improved QISS (IQISS) scheme is implemented on both quantum gray image (FRQI) and quantum color image (MCQI). The new IQISS scheme comprises efficient sharing process and recovering process. The core idea of the sharing process is to combine encryption and measurement for two types of quantum secret images to acquire the quantum shadow images. In the recovering process, strip operation is firstly utilized on the shadow images. Afterwards, the decryption algorithm is used to recover the original quantum secret image. Experiments demonstrate that significant improvements in the security are in favor of the proposed approach. [ABSTRACT FROM AUTHOR]

With the continuous development of quantum computation, quantum mechanics has been widely exploited to meet the storage requirement of high definition image. In this paper, an optimized quantum representation for color digital images (OCQR) is proposed, which makes full use of quantum superposition characteristic to store the RGB value of every pixel. Compared with latest novel quantum representation of color digital images (NCQI), OCQR uses nearly one-third times the qubits to store the pixel value. Meanwhile, some image processing operations related to color information can be executed more simultaneously and conveniently based on OCQR. Therefore, the proposed OCQR model is better suited to represent the quantum color image. [ABSTRACT FROM AUTHOR]

A flexible representation of quantum images (FRQI) was proposed to facilitate the extension of classical (non-quantum)-like image processing applications to the quantum computing domain. The representation encodes a quantum image in the form of a normalized state, which captures information about colors and their corresponding positions in the images. Since its conception, a handful of processing transformations have been formulated, among which are the geometric transformations on quantum images (GTQI) and the CTQI that are focused on the color information of the images. In addition, extensions and applications of FRQI representation, such as multi-channel representation for quantum images (MCQI), quantum image data searching, watermarking strategies for quantum images, a framework to produce movies on quantum computers and a blueprint for quantum video encryption and decryption have also been suggested. These proposals extend classical-like image and video processing applications to the quantum computing domain and offer a significant speed-up with low computational resources in comparison to performing the same tasks on traditional computing devices. Each of the algorithms and the mathematical foundations for their execution were simulated using classical computing resources, and their results were analyzed alongside other classical computing equivalents. The work presented in this review is intended to serve as the epitome of advances made in FRQI quantum image processing over the past five years and to simulate further interest geared towards the realization of some secure and efficient image and video processing applications on quantum computers.

Quantum computation has become increasingly attractive in the past few decades due to its extraordinary performance. As a result, some studies focusing on image representation and processing via quantum mechanics have been done. However, few of them have considered the quantum operations for images restoration. To address this problem, three noise removal algorithms are proposed in this paper based on the novel enhanced quantum representation model, oriented to two kinds of noise pollution (Salt-and-Pepper noise and Gaussian noise). For the first algorithm Q-Mean, it is designed to remove the Salt-and-Pepper noise. The noise points are extracted through comparisons with the adjacent pixel values, after which the restoration operation is finished by mean filtering. As for the second method Q-Gauss, a special mask is applied to weaken the Gaussian noise pollution. The third algorithm Q-Adapt is effective for the source image containing unknown noise. The type of noise can be judged through the quantum statistic operations for the color value of the whole image, and then different noise removal algorithms are used to conduct image restoration respectively. Performance analysis reveals that our methods can offer high restoration quality and achieve significant speedup through inherent parallelism of quantum computation. [ABSTRACT FROM AUTHOR]

One of the most considering matters in the field of quantum information processing is quantum data hiding including quantum steganography and quantum watermarking. This field is an efficient tool for protecting any kind of digital data. In this paper, three quantum color images steganography algorithms are investigated based on Least Significant Bit (LSB). The first algorithm employs only one of the image's channels to cover secret data. The second procedure is based on LSB XORing technique, and the last algorithm utilizes two channels to cover the color image for hiding secret quantum data. The performances of the proposed schemes are analyzed by using software simulations in MATLAB environment. The analysis of PSNR, BER and Histogram graphs indicate that the presented schemes exhibit acceptable performances and also theoretical analysis demonstrates that the networks complexity of the approaches scales squarely. [ABSTRACT FROM AUTHOR]

In this review, we present an overview of the advances made in quantum image processing (QIP) comprising of the image representations, the operations realizable on them, and the likely protocols and algorithms for their applications. In particular, we focus on recent progresses on QIP-based security technologies including quantum watermarking, quantum image encryption, and quantum image steganography. This review is aimed at providing readers with a succinct, yet adequate compendium of the progresses made in the QIP sub-area. Hopefully, this effort will stimulate further interest aimed at the pursuit of more advanced algorithms and experimental validations for available technologies and extensions to other domains. [ABSTRACT FROM AUTHOR]

A new quantum multi-channel Red-Green-Blue (RGB) representation for digital images including the preparation and retrieving procedure is proposed. In our method, the images are represented by using two entangled qubit sequences where the first sequence are employed to encode the RGB color information of the pixel and the second one denotes the position of it. The potential applications of the proposed representation, which introduces some useful quantum image processing operators is discussed and supported by software simulations. [ABSTRACT FROM AUTHOR]

Due to the lack of an effective quantum feature extraction method, there is currently no effective way to perform quantum image classification or recognition. In this paper, for the first time, a global quantum feature extraction method based on Schmidt decomposition is proposed. A revised quantum learning algorithm is also proposed that will classify images by computing the Hamming distance of these features. From the experimental results derived from the benchmark database Caltech 101, and an analysis of the algorithm, an effective approach to large-scale image classification is derived and proposed against the background of big data. [ABSTRACT FROM AUTHOR]

Quantum image retrieval is an exhaustive work due to exponential measurements. Casting aside the background of image processing, quantum image is a pure many-body state, and the retrieval task is a physical process named as quantum state tomography. Tomography of a special class of states, permutationally symmetric states, just needs quadratic measurement scales with the number of qubits. In order to take advantage of this result, we propose a method to map the main energy of the image to these states. First, we deduce that $$n+1$$ permutationally symmetric states can be constructed as bases of $$2^n$$ Hilbert space ( n qubits) at least. Second, we execute Schmidt decomposition by continually bipartite splitting of the quantum image (state). At last, we select $$n+1$$ maximum coefficients, do base transformation to map these coefficients to new bases (permutationally symmetric states). By these means, the quantum image with high retrieval performance can be gotten. [ABSTRACT FROM AUTHOR]

Image matching, also known as correspondence problem, can be defined as the establishment of the correspondence between two or more digital images depicting at least partly the same scene. In this paper, we propose a method for matching gray-scale images consisting of quantum information. Quantum template image is directly mapped with quantum reference image, i.e., the quantum register representing each corresponding pixel of the quantum template image is subtracted from that of the quantum reference image by running a quantum subtracter. According to the quantum measurement results, we can save the gray-scale difference and sum all the differences. Then we compare the sum with Tolerance value. If the sum is smaller than Tolerance value, then quantum image matching succeeds. Experimental simulations show that the proposed approach can distinguish any two quantum gray-scale images successfully. Compared to the schemes based on flexible representation of quantum images (FRQI), our approach based on novel enhanced quantum representation of digital images (NEQR) has the advantages of retrieving the original classical image accurately from the quantum image so that it can be generalized to the case where the dimension of quantum template image is smaller than that of quantum reference image. [ABSTRACT FROM AUTHOR]

This paper proposes a new algorithm for binarizing the grayscale quantum images represented by novel enhanced quantum image representation(NEQR) through pixel qubit flipping. The algorithm consists of two steps: the first step performs the qubit state checking, and the second completes pixel qubit flipping based on the results in previous step. The key data analysis shows that our algorithm has the following advantages, which include: (1) Contrasting with the probable algorithm, the result of this paper is deterministic(without error). (2) Comparing with the latest result, our paper has some superior characters: fewer quantum gates, fewer auxiliary qubits and less quantum delay. • Binarization realized with NEQR state has advantages than the previous binarization algorithm: fewer quantum gates, fewer auxiliary qubits and less quantum delay. • Our algorithm is deterministic. That is, no error is introduced into the final binarized quantum state. [ABSTRACT FROM AUTHOR]

Quantum image processing has been a hot issue in the last decade. However, the lack of the quantum feature extraction method leads to the limitation of quantum image understanding. In this paper, a quantum feature extraction framework is proposed based on the novel enhanced quantum representation of digital images. Based on the design of quantum image addition and subtraction operations and some quantum image transformations, the feature points could be extracted by comparing and thresholding the gradients of the pixels. Different methods of computing the pixel gradient and different thresholds can be realized under this quantum framework. The feature points extracted from quantum image can be used to construct quantum graph. Our work bridges the gap between quantum image processing and graph analysis based on quantum mechanics. [ABSTRACT FROM AUTHOR]

In this paper, a novel watermarking scheme for quantum images based on Hadamard transform is proposed. In the new scheme, a unitary transform controlled by a classical binary key is implemented on quantum image. Then, we utilize a dynamic vector, instead of a fixed parameter as in other previous schemes, to control the embedding process. The dynamic embedding vector is decided by both the carrier quantum image and the watermark image, which is only known by the authorized owner. The proposed scheme is analyzed from visual quality, computational complexity, and payload capacity. Analysis and results show that the proposed scheme has better visual quality under a higher embedding capacity and lower complexity compared with other schemes proposed recently. [ABSTRACT FROM AUTHOR]

In this paper, a novel watermarking scheme based on quantum wavelet transform (QWT) is proposed. Firstly, the wavelet coefficients are extracted by executing QWT on quantum image. Then, we utilize a dynamic vector for controlling embedding strength instead of a fixed parameter for embedding process in other schemes. Analysis and results show that the proposed dynamic watermarking scheme has better visual quality under a higher embedding capacity and outperforms the existing schemes in the literature. [ABSTRACT FROM AUTHOR]