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For the synthetic aperture radar (SAR) automatic target recognition problem, we propose a multiview method based on adaptive decision fusion. Considering the possible independence and correlation among multiview SAR images, a clustering algorithm is first performed to divide them into different view sets. In each view set, the included SAR images are assumed to be highly correlated, which can be effectively classified through joint sparse representation. For the output decisions from different view sets, they are assumed to be relatively independent and contribute disproportionally to the recognition result. Therefore, based on the decisions of individual view sets, adaptive weights are decided based on Shannon entropy theory, which are used to linearly fuse the multiple decisions to determine the target label. The MSTAR dataset is employed in experiments, in which both the standard operating condition and some representative extended operating conditions are set up. The performance of the proposed method is studied in comparison with representative state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Fourier ptychographic microscopy (FPM) is a new, developing computational imaging technology. It can realize the quantitative phase imaging of a wide field of view and high-resolution (HR) simultaneously by means of multi-angle illumination via a light emitting diode (LED) array, combined with a phase recovery algorithm and the synthetic aperture principle. However, in the FPM reconstruction process, LED position misalignment affects the quality of the reconstructed image, and the reconstruction efficiency of the existing LED position correction algorithms needs to be improved. This study aims to improve the FPM correction method based on simulated annealing (SA) and proposes a position misalignment correction method (AA-C algorithm) using an improved phase recovery strategy. The spectrum function update strategy was optimized by adding an adaptive control factor, and the reconstruction efficiency of the algorithm was improved. The experimental results show that the proposed method is effective and robust for position misalignment correction of LED arrays in FPM, and the convergence speed can be improved by 21.2% and 54.9% compared with SC-FPM and PC-FPM, respectively. These results can reduce the requirement of the FPM system for LED array accuracy and improve robustness. [ABSTRACT FROM AUTHOR]

Deep convolutional neural networks (DCNN) are extensively used in image classification. However, it is typically impossible to receive ideal effects if directly using it in synthetic aperture radar (SAR) image target recognition. During the data acquisition process, it is difficult to acquire a large number of labeled training data and to ensure the image targets in the center. To extract the width and height features of SAR images and reduce the computational complexity, we constructed an asymmetric parallel convolution module. The module avoids severe over-fitting due to limited training samples and effectively deals with displacement changes with test samples. Meanwhile, the residual learning method is used in the algorithm to avoid the deep network degradation and improve algorithm recognition accuracy (RA). Experimental results show that the RA of the DCNN with residual-learning-based APCRLNet reaches 99.75% under standard operating conditions, which is superior to existing recognition methods. Furthermore, the algorithm also performs well for incomplete training samples and test samples with displacement changes. [ABSTRACT FROM AUTHOR]

Vibration greatly impairs the imaging quality of airborne synthetic aperture ladar (SAL), so the vibration phase error must be estimated and compensated before imaging. Limited by the laser's average power, the high pulse repetition frequency of the SAL will result in lower peak-power of the laser, thereby reducing the echo signal's single-pulse signal-to-noise ratio (SNR). In the case of a low SNR, the coherence between channels worsens, and the vibration phase-error compensation method based on interferometry is difficult to apply. We analyze the imaging SNR and resolution of the echo signal when the airborne SAL observes noncooperative targets by intentionally broadening the transmitting and receiving beams, discussing the imaging processing flow of the low SNR signal under conditions of beam-broaden and platform vibration. The data processing flow includes the phase correction of the echo signal using the transmitting reference channel signal. Based on the flight parameters of the airborne SAL, the echo was dechirped and narrow-band filtered to reduce noise. After subaperture division, the spatial correlation algorithm was used to estimate and compensate the vibration phase error, and the range-Doppler algorithm was used to achieve strip imaging. At the same time, the phase gradient autofocus algorithm was introduced to improve the focusing effect. The processing results of flight experiment data of the airborne SAL corresponding to noncooperative targets at 1 km demonstrated the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Motion error compensation is a crucial aspect of processing inverse synthetic aperture light detection and ranging data. Motion phase error occurs mainly due to the relative motion between the target and the system, as well as vibration of either the system or the target, which significantly affects the image quality of optical synthetic aperture radar. Since spatial targets usually have a non-cooperative motion state with a high degree of motion parameter uncertainty, accurate estimation of cross-range phase error becomes challenging due to the presence of envelope tilt effect. We propose an adaptive compensation method that handles motion errors of maneuvering targets by estimating and compensating various types of errors introduced by the target motion process. Using the geometric and signal models to analyze error components, a compensation model is established that uses envelope contrast and image entropy as fitness functions. The bat algorithm is employed to solve this error model. Simulation and outdoor experimental results demonstrate that the proposed algorithm offers higher accuracy and better stability compared to traditional optimization algorithms. [ABSTRACT FROM AUTHOR]

A phenomenon, referred to as differential synthetic aperture ladar (DSAL) image inclination, is reported. The phenomenon states that in a stably operating DSAL system, the high-resolution image generated by DSAL technique is possibly inclined in the range direction. The range-inclined DSAL image does not change its resolution but makes the DSAL image differ from the real target structure, resulting in a kind of geometric deformation. Theoretical analysis shows that this inclination phenomenon originates from the geometric setting of the two receiving subapertures in the DSAL hardware and is independent of the target distance. By properly setting the subapertures, this phenomenon could be minimized. Detailed DSAL experimental results verified the theoretical interpretation. Methods to correct the inclined DSAL image are suggested. [ABSTRACT FROM AUTHOR]

A strip-mode side-looking large-aperture synthetic aperture imaging ladar (SAIL) based on freespace optics is designed to experimentally verify the key performances for further airborne application. The optical difficulties in the spatial domain, including optical antenna and imaging resolution for large-aperture SAIL, are considered systematically. The optical antenna consists of a circulated duplex including the tunable transmission and reception channels for the flexible wavefront control. An irradiating beam with a spatial quadratic phase-bias for the suitable and controlled phase history can be transmitted from the transmission channel, and the wavefront aberration in the reception channel resulted from the diffraction can be eliminated for the optimized heterodyne detection. The construction and 2-D imaging algorithm of the SAIL are also proposed. The performances, including wavefront, heterodyne efficiency, field of view, imaging resolution, and 2-D imaging algorithm, have been systemically verified in the short-distance of laboratory space. The well-focused 2-D SAIL imaging of a diffusely scattering target with submillimeter imaging resolution is given. The experimental results are in good agreement with the theoretical design. The results have the great significance for the future development of airborne large-aperture SAIL. [ABSTRACT FROM AUTHOR]

We propose a hybrid approach to image enhancement in acoustic resolution photoacoustic microscopy. The developed technique is based on compensation for nonuniform spatial sensitivity of the optoacoustic (OA) system in both optical and acoustic domains. Spatial distribution of optical fluence is derived from full threedimensional Monte Carlo simulations accounting for conical geometry of tissue laser illumination at the wavelength of 532 nm. Approximate nonuniform spatial response of acoustic detector with numerical aperture of 0.6 is derived from the two-dimensional k-Wave modeling. Application of the developed technique allows to improve the spatial resolution and to balance in-depth signal-level distribution in OA images of phantom and in-vivo objects. [ABSTRACT FROM AUTHOR]

The resolution of an optical imaging system is often limited by various phase aberrations. To get the joint estimation of an object and aberrations of an imaging system with perturbations, a defocused spatial diversity technology with aperture scanning was proposed and evaluated. This technology creates spatial diversity images by scanning an aperture in the defocused plane of the aberrated imaging system. Based on these diversity images, the stochastic parallel gradient descent algorithm was used to recover the phase aberration of the imaging system by adaptively optimizing the coefficients of Zernike polynomials. Then the near-diffraction-limited image of the object can be restored using a multiframe Winner-Helstrom filter. Numerical simulations performed with different phase distributions validated the technology. The technology proposed may be widely used in aberrated imaging systems for aberration detection and image restoration. [ABSTRACT FROM AUTHOR]

The occlusion problem is a major challenge in the field of computer vision. Synthetic aperture imaging (SAI) is often used for surface reconstruction of occluded objects. However, SAI usually relies on high-speed information transmission devices. In addition, a large amount of information in the scene is lost, when handling low-resolution input images. This limitation results in unclear reconstructed regions in the synthetic aperture image and thus hinders the application of SAI in downstream tasks. We propose a multi-view super-resolution SAI method. It aims to generate high-resolution synthetic aperture images using images acquired by few of low-resolution acquisition devices. The main contributions of this paper are: (1) a multi-view super-resolution algorithm is proposed. It can generate clear synthetic aperture images in an array with a limited number of cameras. (2) By exploiting the correlation between views, the proposed algorithm can generate super-resolution synthetic aperture images with more accurate image structure and sharper image edges. (3) A feature extraction module is proposed. It can effectively extract the complementary relationship between pictures from different perspectives. The experimental results show that the proposed method can generate a reconstructed image of the occluded object surface with clear edges and accurate structure. Compared to conventional SAI, our method improves 5.7 % / 21.1 % on peak signal-to-noise ratio (PSNR)/structure similarity index measure (SSIM) and 4.4 % / 9.2 % on PSNR/SSIM respectively on two datasets compared to other state-of-the-art super-resolution methods. [ABSTRACT FROM AUTHOR]

The image scene is limited by the small size of the spot, which is linked with the short wavelength of the laser in synthetic aperture ladar (SAL). The common wide-scene imaging mode in synthetic aperture radar, i.e., the terrain observation by progressive scans imaging mode, is extended and applied in SAL. A suitable imaging algorithm is also proposed according to the characteristics of the signal. First, the azimuth prefiltering based on the spectrum analysis is adopted to eliminate the azimuth spectrum aliasing caused by the steering of the antenna beam. Then, the improved frequency scaling algorithm is applied to complete the range compression and range cell migration correction. Meanwhile, the Doppler frequency shift induced by the continuous moving of the platform is compensated. Finally, the azimuth compression is completed in the Doppler domain, and the SAL image without ambiguity is obtained with the application of the dechirp technique. Simulation results provide the evidence on the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A key requirement to put terahertz (THz) imaging systems into applications is high resolution. Based on a self-developed THz quantum cascade laser (QCL), we demonstrate a THz inline digital holography imaging system with high lateral resolution. In our case, the lateral resolution of this holography imaging system is pushed to about 70 μm, which is close to the intrinsic resolution limit of this system. To the best of our knowledge, this is much smaller than what has been reported up to now. This is attributed to a series of improvements, such as shortening the QCL wavelength, increasing Nx and Ny by the synthetic aperture method, smoothing the source beam profile, and diminishing vibration due to the cryorefrigeration device. This kind of holography system with a resolution smaller than 100 μm opens the door for many imaging experiments. It will turn the THz imaging systems into applications. [ABSTRACT FROM AUTHOR]

This paper describes a way to synthesize a larger coherent aperture from smaller apertures combined with motion, when only intensities are measured. It relies on collecting intensity patterns in two planes for each aperture, for example, the aperture plane and an image plane, and using a phase-retrieval algorithm to reconstruct the optical field in the aperture plane. As the sensor moves forward, a larger two-dimensional aperture is synthesized, allowing a much finer resolution image to be reconstructed. An algorithm to correct for the relative pointing (tip and tilt phases) and piston errors between different apertures and at different times is needed to phase up the synthetic aperture. Results of simulations, including the effects of speckle, are shown, and practical considerations are evaluated. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) image despeckling is a preprocessing method. SAR images are, by default, noisy in nature. The kind of noise found in SAR images is called speckle noise. The effect of this noise on SAR images is highly adverse. It degrades the quality of the SAR image, resulting in the loss of vital information. Since SAR images are inherently speckled in nature, it costs a lot of information loss. The removal of such noise from the SAR image is mandatory and is the first step. The elimination of speckle noise from SAR images is called SAR image despeckling. There are various traditional and nontraditional methods of SAR image despeckling based on Bayesian and non-Bayesian techniques. The SAR image despeckling methods based on Bayesian techniques are further subdivided into spatial and transform domains. This paper presents a comparative review of nontraditional perspectives on SAR image despeckling. The comparison is made based on methodology, objectives, merits, and demerits. Its focus is to do analysis of all the latest research done in the field of SAR image despeckling using nontraditional methods. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence and synthetic aperture radar (SAR) imaging technology, methods based on deep learning have been gradually applied to SAR image aircraft detection. However, due to the special SAR imaging mechanism, the imaging results of aircraft targets in SAR images do not have clear features and appear as sparse scattering centers. In addition, airports contain strongly scattering buildings and objects, such as corridor bridges, which will bring huge interference to SAR aircraft target detection. To alleviate these problems, we propose an aircraft scattering information extraction and detection model (SIEDM) based on the spatial imaging characteristics of the targets. First, a scattering center feature extraction module is designed to extract the potential scattering centers of the aircraft targets in the SAR images and acquire the overall structural features of the aircraft targets. In addition, the adaptive noise suppression module is proposed to suppress background interference by learning global information. Finally, we conduct a series of experiments on an SAR image aircraft detection dataset. The experimental results show that the mean average precision of the aircraft SIEDM is 95.7%, which is better than other methods, and the proposed modules in this paper are effective. [ABSTRACT FROM AUTHOR]

Guest Editors Achyut Shankar, Li Zhang, Yu Chen Hu, and Prabhishek Singh introduce the Special Section on Synthetic Aperture Radar Imaging Technology in Deep Learning: New Trends and Viewpoints. [ABSTRACT FROM AUTHOR]

Based on photonic integrated circuit (PIC) technology and synthetic aperture technology, the advanced technology of segmented planar imaging, which can be used to realize ultrathin and high-resolution imaging, is proposed. We develop a sampling lens array structure that combines coherent detection and traditional imaging; it can improve the sampling of low- and medium-frequency information. Based on the proposed lens array structure, a full-chain simulation model of the segmented planar imaging system is established. Under the premise of similar imaging quality, compared with the existing sampling lens structures, the proposed lens array has a simpler structure, lower processing difficulty, and lower cost. The simulation analyses of the duty ratio of the lens array, the light splitting number of PIC arrayed waveguide gratings, and the radius of the single lens are carried out. The simulation results provide a certain reference value for the optimal design of the segmented planar optical imaging system and further prove the advantages of the proposed structure. [ABSTRACT FROM AUTHOR]

Targets of interest are different in various applications in which manmade targets, such as aircraft, ships, and buildings, are given more attention. Manmade target extraction methods using synthetic aperture radar (SAR) images are designed in response to various demands, which include civil uses, business purposes, and military industries. This plays an increasingly vital role in monitoring, military reconnaissance, and precision strikes. Achieving accurate and complete results through traditional methods is becoming more challenging because of the scattered complexity of polarization in polarimetric synthetic aperture radar (PolSAR) image. A multistage decision-based method is proposed composed of power decision, dominant scattering mechanism decision, and reflection symmetry decision. In addition, the theories of polarimetric contrast enhancement, generalized Y decomposition, and maximum eigenvalue ratio are applied to assist the decision. Fully PolSAR data are adopted to evaluate and verify the approach. Experimental results show that the method can achieve an effective result with a lower false alarm rate and clear contours. Finally, on this basis, a universal framework of change detection for manmade targets is presented as an application of our method. Two sets of measured data are also used to evaluate and verify the effectiveness of the change-detection algorithm. ©2016 SPIE and IS&T [DOI:10.1117/1.JEI.25.5.053017] [ABSTRACT FROM AUTHOR]

In digital holographic microscopy, the aperture synthesis technique improves resolution by extending the Fourier spectral area beyond the numerical aperture of the objective lens. We propose a method to locate the shifted spectra with subpixel accuracy at high speed. When spectra are synthesized at wrong locations, the synthesized image is distorted, for example, the intensity in the outer area is attenuated, limiting the field of view. We propose an accuracy criterion for the location of the spectra required to reduce this effect below a certain level. Then we calculated each spectral shift from the unscattered component with subpixel accuracy and resampled them so that their spacing became an integer in pixels. We demonstrated this method experimentally and achieved high-quality synthesized image with uniform intensity over the entire area. This method is fast compared to the others because the data used in the calculation are small and the process is simple. [ABSTRACT FROM AUTHOR]

We propose an improved version of a synthetic aperture focusing technique (SAFT) based on a delaymultiply- and-sum algorithm for acoustic-resolution photoacoustic microscopy (AR-PAM). In this method, the photoacoustic (PA) signals from multiple scan-lines are combinatorially coupled, multiplied, and then summed. This process can be considered a correlation operation of the PA signals in each scan-line, so the spatial coherent information between the PA signals can be efficiently extracted. By applying this method in conventional ARPAM, lateral resolution and signal-to-noise ratio in out-of-focus regions are much improved compared with those estimated from the previously developed SAFT, respectively, thereby achieving the extension of the imaging focal region. Our phantom and in vivo imaging experiments prove the validity of our proposed method. [ABSTRACT FROM AUTHOR]

Today, spatial light modulators (SLMs) offer the world of digital holography a robust technology that can be incorporated into hologram recorders. This review surveys recent developments related to the role of SLMs in a family of incoherent digital hologram recorders termed Fresnel incoherent correlation holography (FINCH). Two systems branching out from FINCH, and discussed herein, are a confocal version of FINCH and a synthetic aperture FINCH-based system [ABSTRACT FROM AUTHOR]

Conventional ultrasound (US) and photoacoustic (PA) multimodality imaging require the use of a US pulse for US data acquisition and a laser pulse for PA data acquisition. We propose a method for concurrent US and PA data acquisition with a single-laser pulse. A light-absorbing multilayer film that can generate a US pulse based on the thermoelastic effect is used. The selection of appropriate layer thickness, interlayer spacing, and absorption coefficient allows the spectral characteristics of the generated US signal to be adjusted so that it does not overlap with the spectrum of the PA signal generated by the light transmitting through the layer. Thus, the US signal and the PA signal can be generated, received, and separated by using a single-laser pulse combined with spectral filtering. This method is demonstrated using a multilayer film that generates US signals with a center frequency of 24.2 MHz and fractional bandwidth of 26.8%. The synthetic-aperture focusing technique is applied to improve the lateral resolution and the signal-to-noise ratio. A cyst-like phantom and a film phantom were used to demonstrate the feasibility of this method of concurrent PA-US imaging using single-laser pulses. [ABSTRACT FROM AUTHOR]

Generative adversarial networks (GANs) are utilized for synthetic aperture radar (SAR) image super-resolution reconstruction, affording realistic texture details. However, existing GANs only discriminate the final generated high-resolution (HR) image after two consecutive upsampling processes, which ignore some high-frequency information of the reconstructed images. To resolve this issue, a multiresolution fusion discrimination (MRFD) algorithm is proposed to discriminate the reconstructed feature maps after each upsampling. First, a multiresolution discrimination process discriminates the authenticity of each upsampled feature map separately, which reduces the image distortion imposed during two consecutive upsampling processes. Besides, multiresolution feature fusion further preserves the consistent high-frequency texture structures. Finally, a multiscale dense network extracts image features in different scales, with multiscale dense block's dense connections improving parameter utilization. The experimental results on a SAR dataset demonstrate that the proposed MRFD algorithm performs better in reconstructing the texture details of HR images. [ABSTRACT FROM AUTHOR]

Through theoretical analysis, we have previously proposed a method to measure an isoplanatic angle over a finite distance using three receiver apertures and a synthetic point source. Here, we present the validation experiment for this method. Through careful experimental design, the atmospheric coherence length for spherical waves propagating in the opposite direction was measured and converted to an isoplanatic angle as the true value for comparison. In general, the direct measurement of an isoplanatic angle agrees well with the true value in clear-air periods. Experimental results confirm our method for measuring an isoplanatic angle over a finite distance. The experiment resulted in the first time-diagram of an isoplanatic angle in finite distance ever measured through spherical-wave scintillation. [ABSTRACT FROM AUTHOR]

Background: A unique extreme ultraviolet (EUV-) scanner with a high numerical aperture (NA) of 0.55 was designed to enable printing of resolution lines with 8 nm half-pitch in a single exposure. The introduction of a central obscuration in the optics design reduces the angular load on the multilayer mirrors, enabling a high transmission and throughput. The central obscuration area has been minimized for best imaging, overlay, and transmission. Aim: The wavefront is only available in the non-obscured area. This raises the question of how to describe such a wavefront. Approach: We discuss the choice of fringe-Tatian basis functions to represent the wavefront for an obscured pupil. To make this choice, one needs to balance mathematical correctness while maintaining a simple and intuitive description. Results: We provide a detailed analysis for selecting basis functions that are adequate to describe measured wavefronts on the non-obscured part of the pupil. This statement is supported by imaging simulations. A fast and stable evaluation of the chosen basis functions is presented. An adapted definition of the wavefront root-mean-square deviation for these functions is proposed; it has the advantage of being simple and independent of the number of basis functions used. Conclusions: Because of the benefits of the proposed representation, the community is encouraged to use the same formalism. [ABSTRACT FROM AUTHOR]

We propose the synthetic aperture wavefront sensing approach. It is based on acquiring several sets of measurements of the wavefront slopes by displacing sequentially the microlens array with respect to the unknown wavefront. These measurements are stacked together and processed as if obtained with a single-sampling array with an effective number of subpupils equal to the product of the number of microlenses by the number of displacements. We analyze and compare the performance of this approach with the method of modal coefficient averaging. The comparison is made in terms of the squared wavefront reconstruction error, spatially averaged over the pupil and statistically averaged over the noise and the aberrations of the population.We focused our attention on its applications to eye aberrometry. Our numerical results were obtained for a population statistics consistent with a wide sample of young adult eyes using different sampling grids and with several signal-to-noise ratios. They indicate that the synthetic aperture wavefront sensing is affected by less bias and noise propagation than the averaging method, providing smaller mean-squared estimation error. The number of complete Zernike radial orders that can be estimated using the synthetic aperture approach is consistently higher than that allowed by the conventional method [ABSTRACT FROM AUTHOR]

A new aperture-synthesis approach in femtosecond-pulse digital holography for obtaining a high-resolution and a whole field of view of the reconstructed image is proposed. The subholograms are recorded only by delay scanning holograms that have different delay times between the object and reference beams. In addition, by using image processing techniques, the synthesis aperture digital hologram can be superposed accurately. Analysis and experimental results show that the walk-off in femtosecond off-axis digital holography caused by low coherent can be well eliminated. The resolution and the field of view of the reconstructed image can be improved effectively. [ABSTRACT FROM AUTHOR]

With regard to inverse synthetic aperture radar imaging with limited bandwidth and sparse aperture, it is a challenge to traditional range-Doppler (RD) algorithm. We proposed an innovative two-dimensional (2D) joint sparse imaging algorithm, namely, 2D fast orthogonal matching pursuit (2D-FOMP) algorithm. In the proposed algorithm, one-dimensional OMP (1D-OMP) is extended to 2D-OMP in the complex domain from three aspects of atom recognition, projection update, and residual update. Then, the equivalence between 1D-OMP and 2D-OMP is analyzed theoretically. Meanwhile, two strategies that multi atom recognition and matrix recursive update are added in 2D-OMP to further improve the reconstruction speed of 2D-FOMP. Experimental results based on both simulated and measured data demonstrate that the proposed algorithm has good imaging performance under noisy and sparse conditions. [ABSTRACT FROM AUTHOR]

In testing of high-numerical-aperture spherical lenses, conventional Fizeau interferometry with a mechanical phase modulator suffers from spatial nonuniformity of the phase steps within the observation aperture. The amount of phase modulation decreases rapidly in the marginal region of the aperture due to a geometrical effect, which results in a systematic error of several nanometers in the measured object profile. We propose a synthesis of phase-shifting algorithms in which several algorithms designed for different phase steps operate on the same set of interference fringes recorded in a single phase-shift sequence. Then, the object phase is determined from each of the algorithms for each aperture division. The resultant phase distribution showed minimal systematic errors. [ABSTRACT FROM AUTHOR]

We explore the blending of model-based and deep learning approaches for target recognition in inverse synthetic aperture radar (ISAR) imagery. It evaluates five different approaches, namely, a model-based geometric hashing approach, a supervised deep learning approach, and three different blending models that fuse the model-based and deep learning approaches. The model-based approach extracts scattering centers as features and requires domain experts to identify and characterize important features of a target, which makes the training process very costly and hard to generalize when the image quality degrades in low signal-to-interference-plus-noise-ratio conditions. Next, a deep learning algorithm using a convolutional neural network is considered to extract the spatial features when raw ISAR data are used as input. This approach does not need an expert and only requires the labels of images for training. Finally, three model-based and deep learning approaches are blended together at the feature level and decision level to benefit from the advantages of both approaches, achieving a higher performance. The results show that the blending of the two approaches achieves a high performance while providing explainable inferences. The performance of the five different approaches is evaluated under varying conditions of occlusion, clutter, masking of the target, and adversarial attacks. It is empirically shown that the model-based and deep learning approaches are able to complement each other and can achieve better classification accuracy upon fusing the integrated approach. [ABSTRACT FROM AUTHOR]

Time–frequency analysis is a fundamental tool in many applications, such as inverse synthetic aperture radar (ISAR) imaging along the cross-range direction. Traditional time–frequency transformations designed for the general signal suffer low time–frequency resolution or cross-term interference. In this study, a cascaded UNet-like network is applied to the refinement of basic transformations, and another forward regression network is proposed to estimate the signal parameters directly. Both networks can incorporate a priori information and combine different time–frequency transformations efficiently. Several experiments, especially in the ISAR application, are presented to validate the methods. Through this research, the neural network is a promising approach to develop a customized method with high performance for a specific signal processing problem. [ABSTRACT FROM AUTHOR]

Digital in-line holographic microscopy (DIHM) is a modern approach capable of achieving micron-range lateral and depth resolutions in three-dimensional imaging. DIHM in combination with numerical imaging reconstruction uses an extremely simplified setup while retaining the advantages provided by holography with enhanced capabilities derived from algorithmic digital processing. We introduce superresolved DIHM incoming from time and angular multiplexing of the sample spatial frequency information and yielding in the generation of a synthetic aperture (SA). The SA expands the cutoff frequency of the imaging system, allowing submicron resolutions in both transversal and axial directions. The proposed approach can be applied when imaging essentially transparent (low-concentration dilutions) and static (slow dynamics) samples. Validation of the method for both a synthetic object (U.S. Air Force resolution test) to quantify the resolution improvement and a biological specimen (sperm cells biosample) are reported showing the generation of high synthetic numerical aperture values working without lenses. [ABSTRACT FROM AUTHOR]

We describe the wavefront measurement interferometry technologies suitable for microlenses. It is common for microlenses to exhibit large aberrations and microlens arrays can introduce additional negative effects from the array when the wavefront aberration is measured. In the case of a microlens array, stray light may be generated by the rest of the microlenses during measurement. A single-pass interferometer, such as the Mach–Zehnder interferometer, is a good solution. It is sometimes difficult to maintain a conjugate condition due to large aberrations when a double-pass interferometer, such as a Fizeau interferometer, is used. Interferometers usually use a software aperture to define the calculation area for wavefront aberration measurement. But we determine the effectiveness of the hardware aperture in reducing the noise in the interferometer optics compared to the use of the software aperture. The result of a theoretical investigation shows the effects of the hardware, and the software apertures are almost the same. An experimental investigation is also made using a Mach–Zehnder interferometer with both hardware and software apertures. The hardware aperture is inserted into the interferometer optics and is projected to reduce the effective size of aperture on the pupil of the microlens to avoid the Fresnel diffraction. Finally, the theoretical and experimental results show good correspondence. We show the necessity of the wavefront aberration measurement interferometer technologies for microlenses. [ABSTRACT FROM AUTHOR]

The anomalous spectral behaviors of a chirped Gaussian pulsed beam diffracted by an annular aperture in the turbulent atmosphere are studied. On the basis of the extended Huygens–Fresnel principle and by introducing a hard aperture function into a finite sum of complex Gaussian functions, the approximate analytical expression for the spectral intensity of chirped Gaussian pulses diffracted by an annular aperture in the turbulent atmosphere is derived. The corresponding expressions for a circular aperture, a circular black screen, and the unapertured case are given as special cases of the general results. The relative spectral shift of diffracted chirped Gaussian pulses in the turbulent atmosphere versus the different values of the radius of the annular aperture and the different values of the position parameter are also studied and illustrated with numerical calculations. The results of this work have potential applications in information encoding and transmission in a turbulent atmosphere. [ABSTRACT FROM AUTHOR]

A new synthetic aperture radar (SAR) image change detection algorithm was developed using a spatially chaotic model for coherent SAR images. This algorithm is tolerant of misregistration even when the signal-to-noise ratio is low. Despeckling is unnecessary, making the method especially attractive wherever the radiometric changes are subtle. To demonstrate the algorithm’s performance, a varied set of multitemporal polarimetric SAR images was used for testing. As a reference, the simple image difference (DI) technique and the principal-component analysis (PCA) were used for comparison. The proposed method performs very well and can detect minute changes despite the presence of speckle, for which both DI and PCA fail. [ABSTRACT FROM AUTHOR]

Curvature of a multimode optical fiber reduces the numerical aperture and induces radiation losses. We study this phenomenon and we present the “model disadaptation” method to calculate the local numerical aperture and the power attenuation. We exploit the bending effect on the local numerical aperture to propose a new intrinsic optical fiber temperature sensor. The modeling results are experimentally validated for two kinds of optical fibers: a silica-silicone optical fiber and a silica-polymer optical fiber. The simulation and the experimental results are in good accordance and show that the silica-silicone optical fiber sensor can operate between −60 and 152°C with a good response. The silica-polymer optical fiber temperature sensor can sense the temperatures between −249 and 83°C with a good response. [ABSTRACT FROM AUTHOR]