In this paper,we propose a shear high-order gradient(SHOG)operator by combining the shear operator and high-order gradient(HOG)operator.Compared with the HOG operator,the proposed SHOG operator can incorporate more di...In this paper,we propose a shear high-order gradient(SHOG)operator by combining the shear operator and high-order gradient(HOG)operator.Compared with the HOG operator,the proposed SHOG operator can incorporate more directionality and detect more abundant edge information.Based on the SHOG operator,we extend the total variation(TV)norm to shear high-order total variation(SHOTV),and then propose a SHOTV deblurring model.We also study some properties of the SHOG operator,and show that the SHOG matrices are Block Circulant with Circulant Blocks(BCCB)when the shear angle isπ/4.The proposed model is solved efficiently by the alternating direction method of multipliers(ADMM).Experimental results demonstrate that the proposed method outperforms some state-of-the-art non-blind deblurring methods in both objective and perceptual quality.展开更多
The dual-tree complex wavelet transform is a useful tool in signal and image process- ing. In this paper, we propose a dual-tree complex wavelet transform （CWT） based algorithm for image inpalnting problem. Our appr...The dual-tree complex wavelet transform is a useful tool in signal and image process- ing. In this paper, we propose a dual-tree complex wavelet transform （CWT） based algorithm for image inpalnting problem. Our approach is based on Cai, Chan, Shen and Shen＇s framelet-based algorithm. The complex wavelet transform outperforms the standard real wavelet transform in the sense of shift-invariance, directionality and anti-aliasing. Numerical results illustrate the good performance of our algorithm.展开更多
In the field of automatic target recognition and tracking,traditional image complexity metrics,such as statistical variance and signal-to-noise ratio,all focus on single-frame images.However,there are few researches a...In the field of automatic target recognition and tracking,traditional image complexity metrics,such as statistical variance and signal-to-noise ratio,all focus on single-frame images.However,there are few researches about the complexity of image sequence.To solve this problem,a criterion of evaluating image sequence complexity is proposed.Firstly,to characterize this criterion quantitatively,two metrics for measuring the complexity of image sequence,namely feature space similarity degree of global background(FSSDGB)and feature space occultation degree of local background(FSODLB)are developed.Here,FSSDGB reflects the ability of global background to introduce false alarms based on feature space,and FSODLB represents the difference between target and local background based on feature space.Secondly,the feature space is optimized by the grey relational method and relevant features are removed so that FSSDGB and FSODLB are more reasonable to establish complexity of single-frame images.Finally,the image sequence complexity is not a linear sum of the single-frame image complexity.Target tracking errors often occur in high-complexity images and the tracking effect of low-complexity images is very well.The nonlinear transformation based on median(NTM)is proposed to construct complexity of image sequence.The experimental results show that the proposed metric is more valid than other metrics,such as sequence correlation(SC)and interframe change degree(IFCD),and it is highly relevant to the actual performance of automatic target tracking algorithms.展开更多
This paper introduces the complex image concept, and uses the method to analyze multi conductor coplanar waveguides. The method of spectral domain Green's function for modeling point charge and line charge struct...This paper introduces the complex image concept, and uses the method to analyze multi conductor coplanar waveguides. The method of spectral domain Green's function for modeling point charge and line charge structures is studied, in which Chebyshev polynomials are used as basis functions to solve the integral equation by the Galerkin's method. It is believed that the complex method has the features of accuracy and rapid convergence, and it is possible to make the technique useful as CAD tool for coplanar waveguide design.展开更多
基金Supported by the National Natural Science Foundation of China(61701004)Outstanding Young Talents Support Program of Anhui Province(gxyq2021178)+1 种基金Open Fund of Key Laboratory of Anhui Higher Education Institutes(CS2021-07)Program of University Mathematics Teaching Research and Development Center(CMC20200301)。
文摘In this paper,we propose a shear high-order gradient(SHOG)operator by combining the shear operator and high-order gradient(HOG)operator.Compared with the HOG operator,the proposed SHOG operator can incorporate more directionality and detect more abundant edge information.Based on the SHOG operator,we extend the total variation(TV)norm to shear high-order total variation(SHOTV),and then propose a SHOTV deblurring model.We also study some properties of the SHOG operator,and show that the SHOG matrices are Block Circulant with Circulant Blocks(BCCB)when the shear angle isπ/4.The proposed model is solved efficiently by the alternating direction method of multipliers(ADMM).Experimental results demonstrate that the proposed method outperforms some state-of-the-art non-blind deblurring methods in both objective and perceptual quality.
基金Supported by the National Natural Science Foundation of China (10971189, 11001247)the Zhejiang Natural Science Foundation of China (Y6090091)
文摘The dual-tree complex wavelet transform is a useful tool in signal and image process- ing. In this paper, we propose a dual-tree complex wavelet transform （CWT） based algorithm for image inpalnting problem. Our approach is based on Cai, Chan, Shen and Shen＇s framelet-based algorithm. The complex wavelet transform outperforms the standard real wavelet transform in the sense of shift-invariance, directionality and anti-aliasing. Numerical results illustrate the good performance of our algorithm.
基金supported by the National Natural Science Foundation of China(61703337)Shanghai Aerospace Science and Technology Innovation Fund(SAST2017-082)
文摘In the field of automatic target recognition and tracking,traditional image complexity metrics,such as statistical variance and signal-to-noise ratio,all focus on single-frame images.However,there are few researches about the complexity of image sequence.To solve this problem,a criterion of evaluating image sequence complexity is proposed.Firstly,to characterize this criterion quantitatively,two metrics for measuring the complexity of image sequence,namely feature space similarity degree of global background(FSSDGB)and feature space occultation degree of local background(FSODLB)are developed.Here,FSSDGB reflects the ability of global background to introduce false alarms based on feature space,and FSODLB represents the difference between target and local background based on feature space.Secondly,the feature space is optimized by the grey relational method and relevant features are removed so that FSSDGB and FSODLB are more reasonable to establish complexity of single-frame images.Finally,the image sequence complexity is not a linear sum of the single-frame image complexity.Target tracking errors often occur in high-complexity images and the tracking effect of low-complexity images is very well.The nonlinear transformation based on median(NTM)is proposed to construct complexity of image sequence.The experimental results show that the proposed metric is more valid than other metrics,such as sequence correlation(SC)and interframe change degree(IFCD),and it is highly relevant to the actual performance of automatic target tracking algorithms.
基金Supported by the National Natural Science Foundation of China!( 6 96 71 0 1 4)bytheMillimeterWaveStateKeyLaboratoryofSou
文摘This paper introduces the complex image concept, and uses the method to analyze multi conductor coplanar waveguides. The method of spectral domain Green's function for modeling point charge and line charge structures is studied, in which Chebyshev polynomials are used as basis functions to solve the integral equation by the Galerkin's method. It is believed that the complex method has the features of accuracy and rapid convergence, and it is possible to make the technique useful as CAD tool for coplanar waveguide design.
