Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a mult...Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a multi-stage progressive technique called Deep learning based Progressive Joint Source-Channel Coding(DP-JSCC).This approach partitions the source into multiple stages and transmits the signals continuously.The receiver gradually enhances the quality of image reconstruction by progressively receiving the signals,offering greater flexibility compared to existing dynamic rate transmission methods.The model adopts a lightweight architectural design,where we introduce an efficient module called the Inverted Shuffle Attention Bottleneck(ISAB)and incorporate self-attention mechanisms in the encoding and decoding process to capture signal correlations and establish long-range dependencies.Additionally,we introduce the Progressive Focus Weight Allocation(PFWA)method to improve the image reconstruction capability in progressive transmission tasks.These design enhance the expressive capacity of the model.Simulation results demonstrate that DP-JSCC can flexibly adjust the transmission rate according to requirements without the need for retraining or deployment,enabling continuous optimization of signals at different rates.Furthermore,compared to stateof-the-art JSCC methods,DP-JSCC exhibits advantages in terms of computational complexity,parameter count,and reconstruction performance.展开更多
Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborh...Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborhood match method using genetic algorithm is used to conceal the error blocks. Experimental results show that the searching space can be greatly reduced by using genetic algorithm compared with exhaustive searching method, and good image quality is achieved. The peak signal noise ratios(PSNRs) of the restored images are increased greatly.展开更多
Based on the Fisher–Yatess scrambling and DNA coding technology, a chaotical image encryption method is proposed. First, the SHA-3 algorithm is used to calculate the hash value of the initial password, which is used ...Based on the Fisher–Yatess scrambling and DNA coding technology, a chaotical image encryption method is proposed. First, the SHA-3 algorithm is used to calculate the hash value of the initial password, which is used as the initial value of the chaotic system. Second, the chaotic sequence and Fisher–Yatess scrambling are used to scramble the plaintext,and a sorting scrambling algorithm is used for secondary scrambling. Then, the chaotic sequence and DNA coding rules are used to change the plaintext pixel values, which makes the ciphertext more random and resistant to attacks, and thus ensures that the encrypted ciphertext is more secure. Finally, we add plaintext statistics for pixel-level diffusion to ensure plaintext sensitivity. The experimental results and security analysis show that the new algorithm has a good encryption effect and speed, and can also resist common attacks.展开更多
A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. ...A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. Compared with the standard approach of fraetal image coding followed by the Advanced Encryption Standard, our scheme offers a higher sensitivity to both plaintext and ciphertext at a comparable operating efficiency. The keystream generated by the Renyi chaotic map passes the randomness tests set by the United States National Institute of Standards and Technology, and so the proposed scheme is sensitive to the key.展开更多
Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Seco...Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Secondly, an adaptive block partition scheme is introduced by developing the quadtree partition method. Thirdly. a piecewise uniform quantization strategy is appled to quantize the luminance shifting. Finally. experiment results are shown and compared with what reported by Jacquin and Lu to verify the validity of the methods addressed by the authors.展开更多
In order to eliminate float-point operations for fast wavelet transform, an integer D9/7 biorthogonal reversible wavelet transform was accomplished by lifting scheme. The lifting scheme based wavelet transform can be ...In order to eliminate float-point operations for fast wavelet transform, an integer D9/7 biorthogonal reversible wavelet transform was accomplished by lifting scheme. The lifting scheme based wavelet transform can be finished by addition and shift simply. It improved the quality of reconstructive image and greatly reduced the computational complexity due to integer operation. It is suitable for real-time image coding on hardware such as DSP. The simulation results show that the lifting scheme based SPIHT is prior to traditional wavelet based SPHIT in quality and complexity.展开更多
This paper proposes an efficient lossless image compression scheme for still images based on an adaptive arithmetic coding compression algorithm. The algorithm increases the image coding compression rate and ensures t...This paper proposes an efficient lossless image compression scheme for still images based on an adaptive arithmetic coding compression algorithm. The algorithm increases the image coding compression rate and ensures the quality of the decoded image combined with the adaptive probability model and predictive coding. The use of adaptive models for each encoded image block dynamically estimates the probability of the relevant image block. The decoded image block can accurately recover the encoded image according to the code book information. We adopt an adaptive arithmetic coding algorithm for image compression that greatly improves the image compression rate. The results show that it is an effective compression technology.展开更多
A method of digitally high pass filtering in frequency domain is proposed to eliminate the background noise of the decoded image in Fresnel zone plate scanning holography. The high pass filter is designed as a circula...A method of digitally high pass filtering in frequency domain is proposed to eliminate the background noise of the decoded image in Fresnel zone plate scanning holography. The high pass filter is designed as a circular stop, which should be suitable to suppressing the background noise significantly and remain much low frequency information of the object. The principle of high pass filtering is that the Fourier transform of the decoded image is multiplied with the high pass filter. Thus the frequency spectrum of the decoded image without the background noise is achieved. By inverse Fourier transform of the spectrum of the decoded image after multiplying operation, the decoded image without the background noise is obtained. Both of the computer simulations and the experimental results show that the contrast and the signal-to-noise ratio of the decoded image are significantly improved with digital filtering.展开更多
This paper presents a new method for image coding and compressing-ADCTVQ(Adptive Discrete Cosine Transform Vector Quantization). In this method, DCT conforms to visual properties and has an encoding ability which is i...This paper presents a new method for image coding and compressing-ADCTVQ(Adptive Discrete Cosine Transform Vector Quantization). In this method, DCT conforms to visual properties and has an encoding ability which is inferior only to the best transform KLT. Its vector quantization can maintain the minimum quantization distortions and greatly increase the compression ratio. In order to improve compression efficiency, an adaptive strategy of selecting reserved region patterns is applied to preserving the high energy at the same compression ratio. The experiment results show that they are satisfactory at the compression ration ratio if greater than 20.展开更多
The traditional synthetic aperture radar（SAR） image recognition techniques focus on the electro magnetic （EM） scattering centers, ignoring the important role of the shadow information on the SAR image recognition....The traditional synthetic aperture radar（SAR） image recognition techniques focus on the electro magnetic （EM） scattering centers, ignoring the important role of the shadow information on the SAR image recognition. It is difficult to classify targets by the shadow information independently, because the shadow shape is dependent on the radar aspect angle, the depression angle and the resolution. Moreover, the shadow shapes of different targets are similar. When the multiple SAR images of one target from different aspects are available, the performance of the target recognition can be improved. Aimed at the problem, a multi-aspect SAR image recognition technique based on the shadow information is developed. It extracts shadow profiles from SAR images, and takes chain codes as the feature vectors of targets. Then, feature vectors on multiple aspects of the same target are combined with feature sequences, and the hidden Markov model （HMM） is applied to the feature sequences for the target recognition. The simulation result shows the effectiveness of the method.展开更多
With the advancements in nuclear energy,methods that can accurately obtain the spatial information of radioactive sources have become essential for nuclear energy safety.Coded aperture imaging technology is widely use...With the advancements in nuclear energy,methods that can accurately obtain the spatial information of radioactive sources have become essential for nuclear energy safety.Coded aperture imaging technology is widely used because it provides two-dimensional distribution information of radioactive sources.The coded array is a major component of a coded aperture gamma camera,and it affects the key performance parameters of the camera.Currently,commonly used coded arrays such as uniformly redundant arrays(URAs)and modified uniformly redundant arrays(MURAs)have prime numbers of rows or columns and may lead to wastage of detector pixels.A 16×16 coded array was designed on the basis of an existing 16×16 multi-pixel position-sensitive cadmium zinc telluride detector.The digital signal-to-noise(SNR)ratio of the point spread function at the center of the array is 25.67.Furthermore,Monte Carlo camera models and experimental devices based on rank-13 MURA and rank-16 URA have been constructed.With the same angular resolution,the field size of view under rank-16 URA is 1.53 times that of under rank-13 MURA.Simulations(Am-241,Co-57,Ir-192,Cs-137)and experiments(Co-57)are conducted to compare the imaging performance between rank-16 URA and rank-13 MURA.The contrast-to-noise ratio of the reconstructed image of the rank-16 array is great and only slightly lower than that of rank-13 MURA.However,as the photon energy increases,the gap becomes almost negligible.展开更多
Owing to the constraints on the fabrication ofγ-ray coding plates with many pixels,few studies have been carried out onγ-ray computational ghost imaging.Thus,the development of coding plates with fewer pixels is ess...Owing to the constraints on the fabrication ofγ-ray coding plates with many pixels,few studies have been carried out onγ-ray computational ghost imaging.Thus,the development of coding plates with fewer pixels is essential to achieveγ-ray computational ghost imaging.Based on the regional similarity between Hadamard subcoding plates,this study presents an optimization method to reduce the number of pixels of Hadamard coding plates.First,a moving distance matrix was obtained to describe the regional similarity quantitatively.Second,based on the matrix,we used two ant colony optimization arrangement algorithms to maximize the reuse of pixels in the regional similarity area and obtain new compressed coding plates.With full sampling,these two algorithms improved the pixel utilization of the coding plate,and the compression ratio values were 54.2%and 58.9%,respectively.In addition,three undersampled sequences(the Harr,Russian dolls,and cake-cutting sequences)with different sampling rates were tested and discussed.With different sampling rates,our method reduced the number of pixels of all three sequences,especially for the Russian dolls and cake-cutting sequences.Therefore,our method can reduce the number of pixels,manufacturing cost,and difficulty of the coding plate,which is beneficial for the implementation and application ofγ-ray computational ghost imaging.展开更多
We propose a new full color ghost imaging scheme using both time and code division multiplexing technologies.In the scheme,the speckle patterns of three colors(red,green and blue)are modulated with different time slot...We propose a new full color ghost imaging scheme using both time and code division multiplexing technologies.In the scheme,the speckle patterns of three colors(red,green and blue)are modulated with different time slots and codes.The light intensity is sampled by one bucket detector.Then based on the modulated time slots and codes,we can effectively and simultaneously extract three detection component signals corresponding to three color components of objects from the sampling signal of the bucket detector.Finally,three component images resulting from the three component detection signals can be synthesized into a full color image.The experimental results verify the feasibility of our scheme under the limit of the number of time slots and codes.Moreover,our scheme reduces the number of bucket detectors and can realize high quality imaging even in a noisy environment.展开更多
In inertial confinement fusion （ICF）, X-ray coded imaging is considered as the most potential means to diagnose the compressed core. The traditional Richardson-Lucy （RL） method has a strong ability to deblur the i...In inertial confinement fusion （ICF）, X-ray coded imaging is considered as the most potential means to diagnose the compressed core. The traditional Richardson-Lucy （RL） method has a strong ability to deblur the image where the noise follows the Poisson distribution. However, it always suffers from over-fitting and noise amplification, especially when the signal-to-noise ratio of image is relatively low. In this paper, we propose an improved deconvolution method for X-ray coded imaging. We model the image data as a set of independent Gaussian distributions and derive the iterative solution with a maximum-likelihood scheme. The experimental results on X-ray coded imaging data demonstrate that this method is superior to the RL method in terms of anti-overfitting and noise suppression.展开更多
Coded aperture snapshot spectral imaging(CASSI) has been discussed in recent years. It has the remarkable advantages of high optical throughput, snapshot imaging, etc. The entire spatial-spectral data-cube can be reco...Coded aperture snapshot spectral imaging(CASSI) has been discussed in recent years. It has the remarkable advantages of high optical throughput, snapshot imaging, etc. The entire spatial-spectral data-cube can be reconstructed with just a single two-dimensional(2D) compressive sensing measurement. On the other hand, for less spectrally sparse scenes,the insufficiency of sparse sampling and aliasing in spatial-spectral images reduce the accuracy of reconstructed threedimensional(3D) spectral cube. To solve this problem, this paper extends the improved CASSI. A band-pass filter array is mounted on the coded mask, and then the first image plane is divided into some continuous spectral sub-band areas. The entire 3D spectral cube could be captured by the relative movement between the object and the instrument. The principle analysis and imaging simulation are presented. Compared with peak signal-to-noise ratio(PSNR) and the information entropy of the reconstructed images at different numbers of spectral sub-band areas, the reconstructed 3D spectral cube reveals an observable improvement in the reconstruction fidelity, with an increase in the number of the sub-bands and a simultaneous decrease in the number of spectral channels of each sub-band.展开更多
Multispectral time delay and integration charge coupled device （TDICCD） image compression requires a low- complexity encoder because it is usually completed on board where the energy and memory are limited. The Cons...Multispectral time delay and integration charge coupled device （TDICCD） image compression requires a low- complexity encoder because it is usually completed on board where the energy and memory are limited. The Consultative Committee for Space Data Systems （CCSDS） has proposed an image data compression （CCSDS-IDC） algorithm which is so far most widely implemented in hardware. However, it cannot reduce spectral redundancy in mukispectral images. In this paper, we propose a low-complexity improved CCSDS-IDC （ICCSDS-IDC）-based distributed source coding （DSC） scheme for multispectral TDICCD image consisting of a few bands. Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in the original image and its wavelet transformed coefficient. The output of bit plane extractor will be encoded by a first order entropy coder. Low-density parity-check-based Slepian-Wolf （SW） coder is adopted to implement the DSC strategy. Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band.展开更多
Diffractive lenses(DLs)can realize high-resolution imaging with light weight and compact size.Conventional DLs suffer large chromatic and off-axis aberrations,which significantly limits their practical applications.Al...Diffractive lenses(DLs)can realize high-resolution imaging with light weight and compact size.Conventional DLs suffer large chromatic and off-axis aberrations,which significantly limits their practical applications.Although many achromatic methods have been proposed,most of them are used for designing small aperture DLs,which have low diffraction efficiencies.In the designing of diffractive achromatic lenses,increasing the aperture and improving the diffraction efficiency have become two of the most important design issues.Here,a novel phase-coded diffractive lens(PCDL)for achromatic imaging with a large aperture and high efficiency is proposed and demonstrated experimentally,and it also possesses wide field-of-view(FOV)imaging at the same time.The phase distribution of the conventional phase-type diffractive lens(DL)is coded with a cubic function to expand both the working bandwidth and the FOV of conventional DL.The proposed phase-type DL is fabricated by using the laser direct writing of grey-scale patterns for a PCDL of a diameter of 10 mm,a focal length of 100 mm,and a cubic phase coding parameter of 30π.Experimental results show that the working bandwidth and the FOV of the PCDL respectively reach 50 nm and 16°with over 8%focusing efficiency,which are in significant contrast to the counterparts of conventional DL and in good agreement with the theoretical predictions.This work provides a novel way for implementing the achromatic,wide FOV,and high-efficiency imaging with large aperture DL.展开更多
A blind and readable image watermarking scheme using wavelet tree quantization is proposed. In order to increase the algorithm robustness and ensure the watermark integrity,error correction coding techniques are used ...A blind and readable image watermarking scheme using wavelet tree quantization is proposed. In order to increase the algorithm robustness and ensure the watermark integrity,error correction coding techniques are used to encode the embedded watermark. In the watermark embedding process, the wavelet coefficients of the host image are grouped into wavelet trees and each watermark bit is embedded by using two trees. The trees are so quantized that they exhibit a large enough statistical difference, which will later be used for watermark extraction. The experimental results show that the proposed algorithm is effective and robust to common image processing operations and some geometric operations such as JPEG compression, JPEG2000 compression, filtering, Gaussian noise attack, and row-column removal. It is demonstrated that the proposed technique is practical.展开更多
The encoding aperture snapshot spectral imaging system,based on the compressive sensing theory,can be regarded as an encoder,which can efficiently obtain compressed two-dimensional spectral data and then decode it int...The encoding aperture snapshot spectral imaging system,based on the compressive sensing theory,can be regarded as an encoder,which can efficiently obtain compressed two-dimensional spectral data and then decode it into three-dimensional spectral data through deep neural networks.However,training the deep neural net⁃works requires a large amount of clean data that is difficult to obtain.To address the problem of insufficient training data for deep neural networks,a self-supervised hyperspectral denoising neural network based on neighbor⁃hood sampling is proposed.This network is integrated into a deep plug-and-play framework to achieve self-supervised spectral reconstruction.The study also examines the impact of different noise degradation models on the fi⁃nal reconstruction quality.Experimental results demonstrate that the self-supervised learning method enhances the average peak signal-to-noise ratio by 1.18 dB and improves the structural similarity by 0.009 compared with the supervised learning method.Additionally,it achieves better visual reconstruction results.展开更多
文摘Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a multi-stage progressive technique called Deep learning based Progressive Joint Source-Channel Coding(DP-JSCC).This approach partitions the source into multiple stages and transmits the signals continuously.The receiver gradually enhances the quality of image reconstruction by progressively receiving the signals,offering greater flexibility compared to existing dynamic rate transmission methods.The model adopts a lightweight architectural design,where we introduce an efficient module called the Inverted Shuffle Attention Bottleneck(ISAB)and incorporate self-attention mechanisms in the encoding and decoding process to capture signal correlations and establish long-range dependencies.Additionally,we introduce the Progressive Focus Weight Allocation(PFWA)method to improve the image reconstruction capability in progressive transmission tasks.These design enhance the expressive capacity of the model.Simulation results demonstrate that DP-JSCC can flexibly adjust the transmission rate according to requirements without the need for retraining or deployment,enabling continuous optimization of signals at different rates.Furthermore,compared to stateof-the-art JSCC methods,DP-JSCC exhibits advantages in terms of computational complexity,parameter count,and reconstruction performance.
文摘Since real world communication channels are not error free, the coded data transmitted on them may be corrupted, and block based image coding systems are vulnerable to transmission impairment. So the best neighborhood match method using genetic algorithm is used to conceal the error blocks. Experimental results show that the searching space can be greatly reduced by using genetic algorithm compared with exhaustive searching method, and good image quality is achieved. The peak signal noise ratios(PSNRs) of the restored images are increased greatly.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61173183,61672124,61370145,and 11501064)the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund,China(Grant No.MMJJ20170203)+1 种基金the China Postdoctoral Science Foundation(Grant No.2016M590850)the Scientific and Technological Research Program of Chongqing Municipal Education Commission,China(Grant No.KJ1500605)
文摘Based on the Fisher–Yatess scrambling and DNA coding technology, a chaotical image encryption method is proposed. First, the SHA-3 algorithm is used to calculate the hash value of the initial password, which is used as the initial value of the chaotic system. Second, the chaotic sequence and Fisher–Yatess scrambling are used to scramble the plaintext,and a sorting scrambling algorithm is used for secondary scrambling. Then, the chaotic sequence and DNA coding rules are used to change the plaintext pixel values, which makes the ciphertext more random and resistant to attacks, and thus ensures that the encrypted ciphertext is more secure. Finally, we add plaintext statistics for pixel-level diffusion to ensure plaintext sensitivity. The experimental results and security analysis show that the new algorithm has a good encryption effect and speed, and can also resist common attacks.
基金Project supported by the Research Grants Council of the Hong Kong Special Administrative Region,China(Grant No.CityU123009)
文摘A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. Compared with the standard approach of fraetal image coding followed by the Advanced Encryption Standard, our scheme offers a higher sensitivity to both plaintext and ciphertext at a comparable operating efficiency. The keystream generated by the Renyi chaotic map passes the randomness tests set by the United States National Institute of Standards and Technology, and so the proposed scheme is sensitive to the key.
文摘Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Secondly, an adaptive block partition scheme is introduced by developing the quadtree partition method. Thirdly. a piecewise uniform quantization strategy is appled to quantize the luminance shifting. Finally. experiment results are shown and compared with what reported by Jacquin and Lu to verify the validity of the methods addressed by the authors.
基金The Ministerial Level Advanced Research Foundation
文摘In order to eliminate float-point operations for fast wavelet transform, an integer D9/7 biorthogonal reversible wavelet transform was accomplished by lifting scheme. The lifting scheme based wavelet transform can be finished by addition and shift simply. It improved the quality of reconstructive image and greatly reduced the computational complexity due to integer operation. It is suitable for real-time image coding on hardware such as DSP. The simulation results show that the lifting scheme based SPIHT is prior to traditional wavelet based SPHIT in quality and complexity.
基金supported by the National Natural Science Foundation of China (Grant Nos. 60573172 and 60973152)the Superior University Doctor Subject Special Scientific Research Foundation of China (Grant No. 20070141014)the Natural Science Foundation of Liaoning Province of China (Grant No. 20082165)
文摘This paper proposes an efficient lossless image compression scheme for still images based on an adaptive arithmetic coding compression algorithm. The algorithm increases the image coding compression rate and ensures the quality of the decoded image combined with the adaptive probability model and predictive coding. The use of adaptive models for each encoded image block dynamically estimates the probability of the relevant image block. The decoded image block can accurately recover the encoded image according to the code book information. We adopt an adaptive arithmetic coding algorithm for image compression that greatly improves the image compression rate. The results show that it is an effective compression technology.
文摘A method of digitally high pass filtering in frequency domain is proposed to eliminate the background noise of the decoded image in Fresnel zone plate scanning holography. The high pass filter is designed as a circular stop, which should be suitable to suppressing the background noise significantly and remain much low frequency information of the object. The principle of high pass filtering is that the Fourier transform of the decoded image is multiplied with the high pass filter. Thus the frequency spectrum of the decoded image without the background noise is achieved. By inverse Fourier transform of the spectrum of the decoded image after multiplying operation, the decoded image without the background noise is obtained. Both of the computer simulations and the experimental results show that the contrast and the signal-to-noise ratio of the decoded image are significantly improved with digital filtering.
文摘This paper presents a new method for image coding and compressing-ADCTVQ(Adptive Discrete Cosine Transform Vector Quantization). In this method, DCT conforms to visual properties and has an encoding ability which is inferior only to the best transform KLT. Its vector quantization can maintain the minimum quantization distortions and greatly increase the compression ratio. In order to improve compression efficiency, an adaptive strategy of selecting reserved region patterns is applied to preserving the high energy at the same compression ratio. The experiment results show that they are satisfactory at the compression ration ratio if greater than 20.
文摘The traditional synthetic aperture radar（SAR） image recognition techniques focus on the electro magnetic （EM） scattering centers, ignoring the important role of the shadow information on the SAR image recognition. It is difficult to classify targets by the shadow information independently, because the shadow shape is dependent on the radar aspect angle, the depression angle and the resolution. Moreover, the shadow shapes of different targets are similar. When the multiple SAR images of one target from different aspects are available, the performance of the target recognition can be improved. Aimed at the problem, a multi-aspect SAR image recognition technique based on the shadow information is developed. It extracts shadow profiles from SAR images, and takes chain codes as the feature vectors of targets. Then, feature vectors on multiple aspects of the same target are combined with feature sequences, and the hidden Markov model （HMM） is applied to the feature sequences for the target recognition. The simulation result shows the effectiveness of the method.
基金supported by the National Natural Science Foundation of China(No.11675078)the Primary Research and Development Plan of Jiangsu Province(No.BE2017729)the Foundation of Graduate Innovation Center in NUAA(No.kfjj20190614)。
文摘With the advancements in nuclear energy,methods that can accurately obtain the spatial information of radioactive sources have become essential for nuclear energy safety.Coded aperture imaging technology is widely used because it provides two-dimensional distribution information of radioactive sources.The coded array is a major component of a coded aperture gamma camera,and it affects the key performance parameters of the camera.Currently,commonly used coded arrays such as uniformly redundant arrays(URAs)and modified uniformly redundant arrays(MURAs)have prime numbers of rows or columns and may lead to wastage of detector pixels.A 16×16 coded array was designed on the basis of an existing 16×16 multi-pixel position-sensitive cadmium zinc telluride detector.The digital signal-to-noise(SNR)ratio of the point spread function at the center of the array is 25.67.Furthermore,Monte Carlo camera models and experimental devices based on rank-13 MURA and rank-16 URA have been constructed.With the same angular resolution,the field size of view under rank-16 URA is 1.53 times that of under rank-13 MURA.Simulations(Am-241,Co-57,Ir-192,Cs-137)and experiments(Co-57)are conducted to compare the imaging performance between rank-16 URA and rank-13 MURA.The contrast-to-noise ratio of the reconstructed image of the rank-16 array is great and only slightly lower than that of rank-13 MURA.However,as the photon energy increases,the gap becomes almost negligible.
基金supported by the Youth Science Foundation of Sichuan Province(Nos.22NSFSC3816 and 2022NSFSC1231)the General Project of the National Natural Science Foundation of China(Nos.12075039 and 41874121)the Key Project of the National Natural Science Foundation of China(No.U19A2086).
文摘Owing to the constraints on the fabrication ofγ-ray coding plates with many pixels,few studies have been carried out onγ-ray computational ghost imaging.Thus,the development of coding plates with fewer pixels is essential to achieveγ-ray computational ghost imaging.Based on the regional similarity between Hadamard subcoding plates,this study presents an optimization method to reduce the number of pixels of Hadamard coding plates.First,a moving distance matrix was obtained to describe the regional similarity quantitatively.Second,based on the matrix,we used two ant colony optimization arrangement algorithms to maximize the reuse of pixels in the regional similarity area and obtain new compressed coding plates.With full sampling,these two algorithms improved the pixel utilization of the coding plate,and the compression ratio values were 54.2%and 58.9%,respectively.In addition,three undersampled sequences(the Harr,Russian dolls,and cake-cutting sequences)with different sampling rates were tested and discussed.With different sampling rates,our method reduced the number of pixels of all three sequences,especially for the Russian dolls and cake-cutting sequences.Therefore,our method can reduce the number of pixels,manufacturing cost,and difficulty of the coding plate,which is beneficial for the implementation and application ofγ-ray computational ghost imaging.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62001249 and 61871234)the NUPTSF(Grant No.NY220004)the Scientific Research Project of College of Information Engineering,Fuyang Normal University(Grant No.FXG2021ZZ02)。
文摘We propose a new full color ghost imaging scheme using both time and code division multiplexing technologies.In the scheme,the speckle patterns of three colors(red,green and blue)are modulated with different time slots and codes.The light intensity is sampled by one bucket detector.Then based on the modulated time slots and codes,we can effectively and simultaneously extract three detection component signals corresponding to three color components of objects from the sampling signal of the bucket detector.Finally,three component images resulting from the three component detection signals can be synthesized into a full color image.The experimental results verify the feasibility of our scheme under the limit of the number of time slots and codes.Moreover,our scheme reduces the number of bucket detectors and can realize high quality imaging even in a noisy environment.
基金Project supported by the National High-Tech ICF Committee of China,Foundation of China Academy of Engineering Physics(Grant Nos.2009A0102003 and 2011B0102021)the National Natural Science Foundation of China(Grant No.10905051)
文摘In inertial confinement fusion （ICF）, X-ray coded imaging is considered as the most potential means to diagnose the compressed core. The traditional Richardson-Lucy （RL） method has a strong ability to deblur the image where the noise follows the Poisson distribution. However, it always suffers from over-fitting and noise amplification, especially when the signal-to-noise ratio of image is relatively low. In this paper, we propose an improved deconvolution method for X-ray coded imaging. We model the image data as a set of independent Gaussian distributions and derive the iterative solution with a maximum-likelihood scheme. The experimental results on X-ray coded imaging data demonstrate that this method is superior to the RL method in terms of anti-overfitting and noise suppression.
基金supported by the National Natural Science Foundation for Distinguished Young Scholars of China(Grant No.61225024)the National High Technology Research and Development Program of China(Grant No.2011AA7012022)
文摘Coded aperture snapshot spectral imaging(CASSI) has been discussed in recent years. It has the remarkable advantages of high optical throughput, snapshot imaging, etc. The entire spatial-spectral data-cube can be reconstructed with just a single two-dimensional(2D) compressive sensing measurement. On the other hand, for less spectrally sparse scenes,the insufficiency of sparse sampling and aliasing in spatial-spectral images reduce the accuracy of reconstructed threedimensional(3D) spectral cube. To solve this problem, this paper extends the improved CASSI. A band-pass filter array is mounted on the coded mask, and then the first image plane is divided into some continuous spectral sub-band areas. The entire 3D spectral cube could be captured by the relative movement between the object and the instrument. The principle analysis and imaging simulation are presented. Compared with peak signal-to-noise ratio(PSNR) and the information entropy of the reconstructed images at different numbers of spectral sub-band areas, the reconstructed 3D spectral cube reveals an observable improvement in the reconstruction fidelity, with an increase in the number of the sub-bands and a simultaneous decrease in the number of spectral channels of each sub-band.
基金supported by the National High Technology Research and Development Program of China (Grant No. 863-2-5-1-13B)
文摘Multispectral time delay and integration charge coupled device （TDICCD） image compression requires a low- complexity encoder because it is usually completed on board where the energy and memory are limited. The Consultative Committee for Space Data Systems （CCSDS） has proposed an image data compression （CCSDS-IDC） algorithm which is so far most widely implemented in hardware. However, it cannot reduce spectral redundancy in mukispectral images. In this paper, we propose a low-complexity improved CCSDS-IDC （ICCSDS-IDC）-based distributed source coding （DSC） scheme for multispectral TDICCD image consisting of a few bands. Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in the original image and its wavelet transformed coefficient. The output of bit plane extractor will be encoded by a first order entropy coder. Low-density parity-check-based Slepian-Wolf （SW） coder is adopted to implement the DSC strategy. Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band.
基金the National Natural Science Foundation of China(Grant No.61775154)the Natural Science Foundation of the Jiangsu Higher Education Institutions,China(Grant No.18KJB140015)+1 种基金the Priority Academic Program Development of Jiangsu Higher Education Institutions,Chinathe Open Research Fund of CAS Key Laboratory of Space Precision Measurement Technology,China(Grant No.SPMT2021001)。
文摘Diffractive lenses(DLs)can realize high-resolution imaging with light weight and compact size.Conventional DLs suffer large chromatic and off-axis aberrations,which significantly limits their practical applications.Although many achromatic methods have been proposed,most of them are used for designing small aperture DLs,which have low diffraction efficiencies.In the designing of diffractive achromatic lenses,increasing the aperture and improving the diffraction efficiency have become two of the most important design issues.Here,a novel phase-coded diffractive lens(PCDL)for achromatic imaging with a large aperture and high efficiency is proposed and demonstrated experimentally,and it also possesses wide field-of-view(FOV)imaging at the same time.The phase distribution of the conventional phase-type diffractive lens(DL)is coded with a cubic function to expand both the working bandwidth and the FOV of conventional DL.The proposed phase-type DL is fabricated by using the laser direct writing of grey-scale patterns for a PCDL of a diameter of 10 mm,a focal length of 100 mm,and a cubic phase coding parameter of 30π.Experimental results show that the working bandwidth and the FOV of the PCDL respectively reach 50 nm and 16°with over 8%focusing efficiency,which are in significant contrast to the counterparts of conventional DL and in good agreement with the theoretical predictions.This work provides a novel way for implementing the achromatic,wide FOV,and high-efficiency imaging with large aperture DL.
文摘A blind and readable image watermarking scheme using wavelet tree quantization is proposed. In order to increase the algorithm robustness and ensure the watermark integrity,error correction coding techniques are used to encode the embedded watermark. In the watermark embedding process, the wavelet coefficients of the host image are grouped into wavelet trees and each watermark bit is embedded by using two trees. The trees are so quantized that they exhibit a large enough statistical difference, which will later be used for watermark extraction. The experimental results show that the proposed algorithm is effective and robust to common image processing operations and some geometric operations such as JPEG compression, JPEG2000 compression, filtering, Gaussian noise attack, and row-column removal. It is demonstrated that the proposed technique is practical.
基金Supported by the Zhejiang Provincial"Jianbing"and"Lingyan"R&D Programs(2023C03012,2024C01126)。
文摘The encoding aperture snapshot spectral imaging system,based on the compressive sensing theory,can be regarded as an encoder,which can efficiently obtain compressed two-dimensional spectral data and then decode it into three-dimensional spectral data through deep neural networks.However,training the deep neural net⁃works requires a large amount of clean data that is difficult to obtain.To address the problem of insufficient training data for deep neural networks,a self-supervised hyperspectral denoising neural network based on neighbor⁃hood sampling is proposed.This network is integrated into a deep plug-and-play framework to achieve self-supervised spectral reconstruction.The study also examines the impact of different noise degradation models on the fi⁃nal reconstruction quality.Experimental results demonstrate that the self-supervised learning method enhances the average peak signal-to-noise ratio by 1.18 dB and improves the structural similarity by 0.009 compared with the supervised learning method.Additionally,it achieves better visual reconstruction results.
