Jun Zhang

发表

A Markov Random Field Model-Based Approach to Image Interpretation

Jun Zhang, James W. Modestino, J. Modestino, 1992, IEEE Trans. Pattern Anal. Mach. Intell..

The application of the Gibbs-Bogoliubov-Feynman inequality in mean field calculations for Markov random fields

Jun Zhang, Jun Zhang, 1996, IEEE Trans. Image Process..

Expectation-maximization algorithms for image processing using multiscale models and mean- field theory, with applications to laser radar range profiling and segmentation

Jun Zhang, Alan S. Willsky, Andy Tsai, 2001 .

MULTISCALE METHODS AND MEAN FIELD THEORY IN EM PROCEDURES FOR IMAGE PROCESSING

A. Willsky, A. Tsai, Jun Zhang, .

Solution of inverse problems in image processing by wavelet expansion

Gaofeng Wang, Jun Zhang, Guang-Wen Pan, 1995, IEEE Trans. Image Process..

High-Order Total Bounded Variation Model and Its Fast Algorithm for Poissonian Image Restoration

Jun Zhang, Chengzhi Deng, Zhaoming Wu, 2019, Mathematical Problems in Engineering.

the Mean Field Theory in EM Procedures for Markov Random Fields

J. W. Modestino, Jun Zhang, J. Modestino, 1991, Proceedings. 1991 IEEE International Symposium on Information Theory.

Figure-ground separation by a dynamical system

Jun Zhang, Jianhua Liu, Jianbo Gao, 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

Wavelet-Based Multi-scale GVF Snake Model for Image Segmentation

Jun Zhang, Guozheng Wang, Jun Zhang, 2007, ICNC.

Pace recognition: eigenface, elastic matching, and neural nets

Jun Zhang, M. Lades, Yong Yan, 1997, Proc. IEEE.

Image sequence segmentation using 3-D structure tensor and curve evolution

Jun Zhang, Jianbo Gao, Weisong Liu, 2001, IEEE Trans. Circuits Syst. Video Technol..

A model-fitting approach to cluster validation with application to stochastic model-based image segmentation

James W. Modestino, J. Zhang, J. Modestino, 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

A wavelet-based KL-like expansion for wide-sense stationary random processes

Jun Zhang, Gilbert Waiter, Jun Zhang, 1994, IEEE Trans. Signal Process..

Wavelet neural networks for function learning

Jun Zhang, Gilbert G. Walter, Y. Miao, 1995, IEEE Trans. Signal Process..

Poisson image restoration using a novel directional TVp regularization

Chengzhi Deng, Jun Zhang, Pengcheng Li, 2021, Signal Process..

Adaptive Image Restoration via a Relaxed Regularization of Mean Curvature

Jun Zhang, Chengzhi Deng, Jun Zhang, 2020 .

Poisson image denoising based on fractional-order total variation

Jun Zhang, Yifei Lou, Jing Qin, 2020, Inverse Problems & Imaging.

Fast Algorithms for Poisson Image Denoising Using Fractional-Order Total Variation

Jun Zhang, Chengzhi Deng, Mingxi Ma, 2018, ICGEC.

A Markov random field model-based approach to image interpretation

Jun Zhang, James W. Modestino, J. Modestino, 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

The application of mean field theory to image motion estimation

Jun Zhang, Gerald G. Hanauer, Jun Zhang, 1995, IEEE Trans. Image Process..

A wavelet-based multiresolution statistical model for texture

Jun Zhang, Dongyan Wang, Que N. Tran, 1998, IEEE Trans. Image Process..

Cluster validation for unsupervised stochastic model-based image segmentation

Jun Zhang, James W. Modestino, David A. Langan, 1994, Proceedings of 1st International Conference on Image Processing.

Solution of inverse problems in image processing by wavelet expansion

Gaofeng Wang, Jun Zhang, Guang-Wen Pan, 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Parameter reduction for the compound Gauss-Markov model

Jun Zhang, Jun Zhang, 1995, IEEE Trans. Image Process..

The mean field theory in EM procedures for blind Markov random field image restoration

Jun Zhang, Jun Zhang, 1993, IEEE Trans. Image Process..

A segmentation algorithm for SAR images based on the anisotropic heat diffusion equation

Jun Zhang, Lingjun Zhao, Gui Gao, 2008, Pattern Recognit..