Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to ...Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to the degradation of image.This paper presents a fusion framework based on block-matching and 3D(BM3D) multi-scale transform. The algorithm first divides the image into different blocks and groups these 2D image blocks into 3D arrays by their similarity. Then it uses a 3D transform which consists of a 2D multi-scale and a 1D transform to transfer the arrays into transform coefficients, and then the obtained low-and high-coefficients are fused by different fusion rules. The final fused image is obtained from a series of fused 3D image block groups after the inverse transform by using an aggregation process. In the experimental part, we comparatively analyze some existing algorithms and the using of different transforms, e.g. non-subsampled Contourlet transform(NSCT), non-subsampled Shearlet transform(NSST), in the 3D transform step. Experimental results show that the proposed fusion framework can not only improve subjective visual effect, but also obtain better objective evaluation criteria than state-of-the-art methods.展开更多
An improved block matching approach to fast disparity estimation in machine vision applications is proposed, where the matching criterion is the sum of the absolute difference（SAD）.By evaluating the lower bounds, wh...An improved block matching approach to fast disparity estimation in machine vision applications is proposed, where the matching criterion is the sum of the absolute difference（SAD）.By evaluating the lower bounds, which become increasingly tighter for the matching criteria, the method tries to successively terminate unnecessary computations of the matching criteria between the reference block in one image and the ineligible candidate blocks in another image.It also eliminates the ineligible blocks as early as possible, while ensuring the optimal disparity of each pixel.Also, the proposed method can further speed up the elimination of ineligible candidate blocks by efficiently using the continuous constraint of disparity to predict the initial disparity of each pixel.The performance of the new algorithm is evaluated by carrying out a theoretical analysis, and by comparing its performance with the disparity estimation method based on the standard block matching.Simulated results demonstrate that the proposed algorithm achieves a computational cost reduction of over 50.5% in comparision with the standard block matching method.展开更多
MSU Stego Video is a public video steganographic tool, which has strong robustness and is regarded as a real video steganographic tool. In order to increase the detection rate, this paper proposes a new steganoalysis ...MSU Stego Video is a public video steganographic tool, which has strong robustness and is regarded as a real video steganographic tool. In order to increase the detection rate, this paper proposes a new steganoalysis method against MSU, which uses the chessboard character of MSU embedded video, proposes a down-sample block-based collusion method to estimate the original frame and checks the chessboard mode of the different frame between tested frame and estimated frame to detect MSU steganographic evidences. To reduce the error introduced by severe movement of the video content, a method that abandons severe motion blocks from detecting is proposed. The experiment results show that the false negative rate of the proposed algorithm is lower than 5%, and the false positive rate is lower than 2%. Our algorithm has significantly better performance than existing algorithms. Especially to the video that has fast motion, the algorithm has more remarkable performance.展开更多
This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for ...This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for the translational motion between video sequences at the same time;As for the rotary motion vector generated in the video sequences, in order to highlight the intensity change of the image sequence, the algorithm firstly conducts Laplace transform for the reference frame, then select a number of characteristics at the image edge to make block matching with the current frame, calculate and compensate for the rotational movement that may exist finally. Through theoretical analysis and simula-tion, we prove that, as for a mixed translational and rotational motion video sequences, the proposed algorithm can reduce required time for block matching computation ,while improving the accuracy of the electronic image stabilization.展开更多
Block matching based 3D filtering methods have achieved great success in image denoising tasks. However the manually set filtering operation could not well describe a good model to transform noisy images to clean imag...Block matching based 3D filtering methods have achieved great success in image denoising tasks. However the manually set filtering operation could not well describe a good model to transform noisy images to clean images. In this paper, we introduce convolutional neural network （CNN） for the 3D filtering step to learn a well fitted model for denoising. With a trainable model, prior knowledge is utilized for better mapping from noisy images to clean images. This block matching and CNN joint model （BMCNN） could denoise images with different sizes and different noise intensity well, especially images with high noise levels. The experimental results demonstrate that among all competing methods, this method achieves the highest peak signal to noise ratio （PSNR） when denoising images with high noise levels （σ 〉 40）, and the best visual quality when denoising images with all the tested noise levels.展开更多
Block-matching and 3D-filtering(BM3D) is a state of the art denoising algorithm for image/video,which takes full advantages of the spatial correlation and the temporal correlation of the video. The algorithm performan...Block-matching and 3D-filtering(BM3D) is a state of the art denoising algorithm for image/video,which takes full advantages of the spatial correlation and the temporal correlation of the video. The algorithm performance comes at the price of more similar blocks finding and filtering which bring high computation and memory access. Area, memory bandwidth and computation are the major bottlenecks to design a feasible architecture because of large frame size and search range. In this paper, we introduce a novel structure to increase data reuse rate and reduce the internal static-random-access-memory(SRAM) memory. Our target is to design a phase alternating line(PAL) or real-time processing chip of BM3 D. We propose an application specific integrated circuit(ASIC) architecture of BM3 D for a 720 × 576 BT656 PAL format. The feature of the chip is with 100 MHz system frequency and a 166-MHz 32-bit double data rate(DDR). When noise is σ = 25, we successfully realize real-time denoising and achieve about 10 d B peak signal to noise ratio(PSNR) advance just by one iteration of the BM3 D algorithm.展开更多
In H.264 encoder, all possible coding modes should be checked to choose the most appropriate mode for every macroblock, which adds a heavy computation burden to the encoder. In this paper, a fast inter-mode decision m...In H.264 encoder, all possible coding modes should be checked to choose the most appropriate mode for every macroblock, which adds a heavy computation burden to the encoder. In this paper, a fast inter-mode decision method is presented to reduce computation complexity of an H.264 encoder. By detecting the best matching block （BMB） before transform and quantization, some coding modes can be skipped and the corresponding encoding steps can be omitted for these BMBs. Meanwhile this method can also be used to detect all-zero blocks. The experimental results show that this method achieves consistently significant reduction of encoding time while keeping almost the same rate-distortion performance.展开更多
This paper proposed a back propagation neural network model for predictive block-matching. Predictive block-matching is a way to significantly decrease the computational complexity of motion estimation, but the tradit...This paper proposed a back propagation neural network model for predictive block-matching. Predictive block-matching is a way to significantly decrease the computational complexity of motion estimation, but the traditional prediction model was proposed 26 years ago. It is straight forward but not accurate enough. The proposed back propagation neural network has 5 inputs, 5 neutrons and 1 output. Because of its simplicity, it requires very little calculation power which is negligible compared with existing computation complexity. The test results show 10% - 30% higher prediction accuracy and PSNR improvement up to 0.3 dB. The above advantages make it a feasible replacement of the current model.展开更多
A collection of k-matchings of bipartite graph Kn,n with the property thatevery pair of independent edges lies in exactly λ of the k-matchings is called aBIMATCH(n,k,λ)-design. Existences and constructions for vario...A collection of k-matchings of bipartite graph Kn,n with the property thatevery pair of independent edges lies in exactly λ of the k-matchings is called aBIMATCH(n,k,λ)-design. Existences and constructions for various BIMATCH (n,k,λ)designs are given.展开更多
Reduction of conservatism is one of the key and difficult problems in missile robust gain scheduling autopilot design based on multipliers.This article presents a scheme of adopting linear parameter-varying（LPV） con...Reduction of conservatism is one of the key and difficult problems in missile robust gain scheduling autopilot design based on multipliers.This article presents a scheme of adopting linear parameter-varying（LPV） control approach with full block multipliers to design a missile robust gain scheduling autopilot in order to eliminate conservatism.A model matching design structure with a high demand on matching precision is constructed based on the missile linear fractional transformation（LFT） model.By applying full block S-procedure and elimination lemma,a convex feasibility problem with an infinite number of constraints is formulated to satisfy robust quadratic performance specifications.Then a grid method is adopted to transform the infinite-dimensional convex feasibility problem into a solvable finite-dimensional convex feasibility problem,based on which a gain scheduling controller with linear fractional dependence on the flight Mach number and altitude is derived.Static and dynamic simulation results show the effectiveness and feasibility of the proposed scheme.展开更多
This study investigated the problems of non-cooperative target recognition and relative motion estimation during spacecraft rendezvous maneuvers.A structure integrating an Inertial Measurement Unit(IMU)and a visual ca...This study investigated the problems of non-cooperative target recognition and relative motion estimation during spacecraft rendezvous maneuvers.A structure integrating an Inertial Measurement Unit(IMU)and a visual camera was presented.The angular velocity output of the IMU was used to calculate the motion trajectories of star points in multiple image frames,which can highlight the motion of non-cooperative targets with respect to the image background to improve the probability of target recognition.To solve the problem of target misidentification caused by new star points entering the field of view,a target-tracking link based on IMU prediction was introduced to track the position of the target in the image.Furthermore,a measurement model was constructed using the line-of-sight vector generated from target recognition,and the relative motion state was estimated using a Huber-based non-linear filter.Semi-physical and numerical simulations were performed to evaluate the effectiveness and efficiency of the proposed method.展开更多
A novel low-complexity iterative receiver for multiuser space frequency block coding (SFBC) system was proposed in this paper. Unlike the conventional linear minimum mean square error (MMSE) detector, which requires m...A novel low-complexity iterative receiver for multiuser space frequency block coding (SFBC) system was proposed in this paper. Unlike the conventional linear minimum mean square error (MMSE) detector, which requires matrix inversion at each iteration, the soft-in soft-out (SISO) detector is simply a parallel interference cancellation (PIC)-matched filter (MF) operation. The probability density function (PDF) of PIC-MF detector output is approximated as Gaussian, whose variance is calculated with a priori information fed back from the channel decoder. With this approximation, the log likelihood ratios (LLRs) of transmitted bits are under-estimated. Then the LLRs are multiplied by a constant factor to achieve a performance gain. The constant factor is optimized according to extrinsic information transfer (EXIT) chart of the SISO detector. Simulation results show that the proposed iterative receiver can significantly improve the system performance and converge to the matched filter bound (MFB) with low computational complexity at high signal-to-noise ratios (SNRs).展开更多
为应对红外气体泄漏成像过程中因设备转动等因素导致的图像不稳定及泄漏气体检测效果不佳的问题,提出1种结合图像帧子块匹配法和改进快速鲁棒模糊C均值算法(fast and robust fuzzy c-means,FRFCM)的红外图像细节增强方法。该方法利用图...为应对红外气体泄漏成像过程中因设备转动等因素导致的图像不稳定及泄漏气体检测效果不佳的问题,提出1种结合图像帧子块匹配法和改进快速鲁棒模糊C均值算法(fast and robust fuzzy c-means,FRFCM)的红外图像细节增强方法。该方法利用图像帧子块匹配法配准图像帧,同时引入背景建模和差分方法从背景中分离动态气体目标,并在FRFCM基础上增加自适应调整模糊因子以优化图像帧的羽流强化特征效果。研究结果表明:该方法能够有效去除冗余信息,使图像帧匹配误差降低约75%,对比度增强值提高4.7%,羽流分割的平均交并比达到0.68,在保持较高分割准确度的同时显著提升检测速度,适用于油气田、集输站及氢气站等气体安全检测系统。研究结果可为气体泄漏监测技术的优化与应用提供参考。展开更多
基金supported by the National Natural Science Foundation of China(6157206361401308)+6 种基金the Fundamental Research Funds for the Central Universities(2016YJS039)the Natural Science Foundation of Hebei Province(F2016201142F2016201187)the Natural Social Foundation of Hebei Province(HB15TQ015)the Science Research Project of Hebei Province(QN2016085ZC2016040)the Natural Science Foundation of Hebei University(2014-303)
文摘Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to the degradation of image.This paper presents a fusion framework based on block-matching and 3D(BM3D) multi-scale transform. The algorithm first divides the image into different blocks and groups these 2D image blocks into 3D arrays by their similarity. Then it uses a 3D transform which consists of a 2D multi-scale and a 1D transform to transfer the arrays into transform coefficients, and then the obtained low-and high-coefficients are fused by different fusion rules. The final fused image is obtained from a series of fused 3D image block groups after the inverse transform by using an aggregation process. In the experimental part, we comparatively analyze some existing algorithms and the using of different transforms, e.g. non-subsampled Contourlet transform(NSCT), non-subsampled Shearlet transform(NSST), in the 3D transform step. Experimental results show that the proposed fusion framework can not only improve subjective visual effect, but also obtain better objective evaluation criteria than state-of-the-art methods.
基金supported by the Opening Project of State Key Laboratory for Manufacturing Systems EngineeringFoundation for Youth Teacher of School of Mechanical Engineering, Xi’an Jiaotong University Brain Korea 21(BK21) Program of Ministry of Education and Human Resources Development
文摘An improved block matching approach to fast disparity estimation in machine vision applications is proposed, where the matching criterion is the sum of the absolute difference（SAD）.By evaluating the lower bounds, which become increasingly tighter for the matching criteria, the method tries to successively terminate unnecessary computations of the matching criteria between the reference block in one image and the ineligible candidate blocks in another image.It also eliminates the ineligible blocks as early as possible, while ensuring the optimal disparity of each pixel.Also, the proposed method can further speed up the elimination of ineligible candidate blocks by efficiently using the continuous constraint of disparity to predict the initial disparity of each pixel.The performance of the new algorithm is evaluated by carrying out a theoretical analysis, and by comparing its performance with the disparity estimation method based on the standard block matching.Simulated results demonstrate that the proposed algorithm achieves a computational cost reduction of over 50.5% in comparision with the standard block matching method.
基金Supported by the National Natural Science Foundation of China(60970114)Doctoral Fund of Ministry of Education of China(20110141130006)
文摘MSU Stego Video is a public video steganographic tool, which has strong robustness and is regarded as a real video steganographic tool. In order to increase the detection rate, this paper proposes a new steganoalysis method against MSU, which uses the chessboard character of MSU embedded video, proposes a down-sample block-based collusion method to estimate the original frame and checks the chessboard mode of the different frame between tested frame and estimated frame to detect MSU steganographic evidences. To reduce the error introduced by severe movement of the video content, a method that abandons severe motion blocks from detecting is proposed. The experiment results show that the false negative rate of the proposed algorithm is lower than 5%, and the false positive rate is lower than 2%. Our algorithm has significantly better performance than existing algorithms. Especially to the video that has fast motion, the algorithm has more remarkable performance.
文摘This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for the translational motion between video sequences at the same time;As for the rotary motion vector generated in the video sequences, in order to highlight the intensity change of the image sequence, the algorithm firstly conducts Laplace transform for the reference frame, then select a number of characteristics at the image edge to make block matching with the current frame, calculate and compensate for the rotational movement that may exist finally. Through theoretical analysis and simula-tion, we prove that, as for a mixed translational and rotational motion video sequences, the proposed algorithm can reduce required time for block matching computation ,while improving the accuracy of the electronic image stabilization.
基金This research was supported by the National Natural Science Foundation of China under Grant Nos. 61573380 and 61672542, and Fundamental Research Funds for the Central Universities of China under Grant No. 2016zzts055.
文摘Block matching based 3D filtering methods have achieved great success in image denoising tasks. However the manually set filtering operation could not well describe a good model to transform noisy images to clean images. In this paper, we introduce convolutional neural network （CNN） for the 3D filtering step to learn a well fitted model for denoising. With a trainable model, prior knowledge is utilized for better mapping from noisy images to clean images. This block matching and CNN joint model （BMCNN） could denoise images with different sizes and different noise intensity well, especially images with high noise levels. The experimental results demonstrate that among all competing methods, this method achieves the highest peak signal to noise ratio （PSNR） when denoising images with high noise levels （σ 〉 40）, and the best visual quality when denoising images with all the tested noise levels.
基金the National Natural Science Foundation of China(No.61234001)
文摘Block-matching and 3D-filtering(BM3D) is a state of the art denoising algorithm for image/video,which takes full advantages of the spatial correlation and the temporal correlation of the video. The algorithm performance comes at the price of more similar blocks finding and filtering which bring high computation and memory access. Area, memory bandwidth and computation are the major bottlenecks to design a feasible architecture because of large frame size and search range. In this paper, we introduce a novel structure to increase data reuse rate and reduce the internal static-random-access-memory(SRAM) memory. Our target is to design a phase alternating line(PAL) or real-time processing chip of BM3 D. We propose an application specific integrated circuit(ASIC) architecture of BM3 D for a 720 × 576 BT656 PAL format. The feature of the chip is with 100 MHz system frequency and a 166-MHz 32-bit double data rate(DDR). When noise is σ = 25, we successfully realize real-time denoising and achieve about 10 d B peak signal to noise ratio(PSNR) advance just by one iteration of the BM3 D algorithm.
基金Project supported by the National High-Technology Research and Development Program of China (Grant No.2002AA1Z1190)
文摘In H.264 encoder, all possible coding modes should be checked to choose the most appropriate mode for every macroblock, which adds a heavy computation burden to the encoder. In this paper, a fast inter-mode decision method is presented to reduce computation complexity of an H.264 encoder. By detecting the best matching block （BMB） before transform and quantization, some coding modes can be skipped and the corresponding encoding steps can be omitted for these BMBs. Meanwhile this method can also be used to detect all-zero blocks. The experimental results show that this method achieves consistently significant reduction of encoding time while keeping almost the same rate-distortion performance.
文摘This paper proposed a back propagation neural network model for predictive block-matching. Predictive block-matching is a way to significantly decrease the computational complexity of motion estimation, but the traditional prediction model was proposed 26 years ago. It is straight forward but not accurate enough. The proposed back propagation neural network has 5 inputs, 5 neutrons and 1 output. Because of its simplicity, it requires very little calculation power which is negligible compared with existing computation complexity. The test results show 10% - 30% higher prediction accuracy and PSNR improvement up to 0.3 dB. The above advantages make it a feasible replacement of the current model.
文摘A collection of k-matchings of bipartite graph Kn,n with the property thatevery pair of independent edges lies in exactly λ of the k-matchings is called aBIMATCH(n,k,λ)-design. Existences and constructions for various BIMATCH (n,k,λ)designs are given.
文摘Reduction of conservatism is one of the key and difficult problems in missile robust gain scheduling autopilot design based on multipliers.This article presents a scheme of adopting linear parameter-varying（LPV） control approach with full block multipliers to design a missile robust gain scheduling autopilot in order to eliminate conservatism.A model matching design structure with a high demand on matching precision is constructed based on the missile linear fractional transformation（LFT） model.By applying full block S-procedure and elimination lemma,a convex feasibility problem with an infinite number of constraints is formulated to satisfy robust quadratic performance specifications.Then a grid method is adopted to transform the infinite-dimensional convex feasibility problem into a solvable finite-dimensional convex feasibility problem,based on which a gain scheduling controller with linear fractional dependence on the flight Mach number and altitude is derived.Static and dynamic simulation results show the effectiveness and feasibility of the proposed scheme.
基金funded by the China Postdoctoral Science Foundation(No.2023M730337)。
文摘This study investigated the problems of non-cooperative target recognition and relative motion estimation during spacecraft rendezvous maneuvers.A structure integrating an Inertial Measurement Unit(IMU)and a visual camera was presented.The angular velocity output of the IMU was used to calculate the motion trajectories of star points in multiple image frames,which can highlight the motion of non-cooperative targets with respect to the image background to improve the probability of target recognition.To solve the problem of target misidentification caused by new star points entering the field of view,a target-tracking link based on IMU prediction was introduced to track the position of the target in the image.Furthermore,a measurement model was constructed using the line-of-sight vector generated from target recognition,and the relative motion state was estimated using a Huber-based non-linear filter.Semi-physical and numerical simulations were performed to evaluate the effectiveness and efficiency of the proposed method.
基金The Science and Technology Committee of Shanghai Municipality ( No 06DZ15013,No03DZ15010)
文摘A novel low-complexity iterative receiver for multiuser space frequency block coding (SFBC) system was proposed in this paper. Unlike the conventional linear minimum mean square error (MMSE) detector, which requires matrix inversion at each iteration, the soft-in soft-out (SISO) detector is simply a parallel interference cancellation (PIC)-matched filter (MF) operation. The probability density function (PDF) of PIC-MF detector output is approximated as Gaussian, whose variance is calculated with a priori information fed back from the channel decoder. With this approximation, the log likelihood ratios (LLRs) of transmitted bits are under-estimated. Then the LLRs are multiplied by a constant factor to achieve a performance gain. The constant factor is optimized according to extrinsic information transfer (EXIT) chart of the SISO detector. Simulation results show that the proposed iterative receiver can significantly improve the system performance and converge to the matched filter bound (MFB) with low computational complexity at high signal-to-noise ratios (SNRs).
文摘为应对红外气体泄漏成像过程中因设备转动等因素导致的图像不稳定及泄漏气体检测效果不佳的问题,提出1种结合图像帧子块匹配法和改进快速鲁棒模糊C均值算法(fast and robust fuzzy c-means,FRFCM)的红外图像细节增强方法。该方法利用图像帧子块匹配法配准图像帧,同时引入背景建模和差分方法从背景中分离动态气体目标,并在FRFCM基础上增加自适应调整模糊因子以优化图像帧的羽流强化特征效果。研究结果表明:该方法能够有效去除冗余信息,使图像帧匹配误差降低约75%,对比度增强值提高4.7%,羽流分割的平均交并比达到0.68,在保持较高分割准确度的同时显著提升检测速度,适用于油气田、集输站及氢气站等气体安全检测系统。研究结果可为气体泄漏监测技术的优化与应用提供参考。
