Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency
暂无分享,去创建一个
[1] Martin J. Wainwright,et al. Scale Mixtures of Gaussians and the Statistics of Natural Images , 1999, NIPS.
[2] David L. Donoho,et al. De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.
[3] I. Johnstone,et al. Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .
[4] Robert M. Gray,et al. Text and picture segmentation by the distribution analysis of wavelet coefficients , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).
[5] Kannan Ramchandran,et al. Low-complexity image denoising based on statistical modeling of wavelet coefficients , 1999, IEEE Signal Processing Letters.
[6] Hyvarinen. Sparse code shrinkage: denoising of nongaussian data by maximum likelihood estimation , 1999, Neural computation.
[7] Guoliang Fan,et al. Image denoising using a local contextual hidden Markov model in the wavelet domain , 2001, IEEE Signal Processing Letters.
[8] Edward H. Adelson,et al. Noise removal via Bayesian wavelet coring , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.
[9] Y. Benjamini,et al. Adaptive thresholding of wavelet coefficients , 1996 .
[10] Pierre Moulin,et al. Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients , 2001, IEEE Trans. Image Process..
[11] A. Öztürk,et al. Non-Gaussian random vector identification using spherically invariant random processes , 1993 .
[12] Martin Vetterli,et al. Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..
[13] Aapo Hyvärinen,et al. Sparse Code Shrinkage: Denoising of Nongaussian Data by Maximum Likelihood Estimation , 1999, Neural Computation.
[14] Simon Haykin,et al. Image Denoising by Sparse Code Shrinkage , 2001 .
[15] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[16] K. R. Subramanian,et al. Efficient wavelet-based image denoising algorithm , 2001 .
[17] Robert D. Nowak,et al. Wavelet-based image estimation: an empirical Bayes approach using Jeffrey's noninformative prior , 2001, IEEE Trans. Image Process..
[18] Touradj Ebrahimi,et al. The JPEG2000 still image coding system: an overview , 2000, IEEE Trans. Consumer Electron..
[19] Robert D. Nowak,et al. Wavelet-based statistical signal processing using hidden Markov models , 1998, IEEE Trans. Signal Process..
[20] Jerome M. Shapiro,et al. Embedded image coding using zerotrees of wavelet coefficients , 1993, IEEE Trans. Signal Process..
[21] N. Kingsbury. Image processing with complex wavelets , 1999, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.
[22] Hong-Ye Gao,et al. Wavelet Shrinkage Denoising Using the Non-Negative Garrote , 1998 .
[23] B. Silverman,et al. Incorporating Information on Neighboring Coefficients Into Wavelet Estimation , 2001 .
[24] D J Field,et al. Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.
[25] Eero P. Simoncelli,et al. Image denoising using a local Gaussian scale mixture model in the wavelet domain , 2000, SPIE Optics + Photonics.
[26] Martin Vetterli,et al. Spatially adaptive wavelet thresholding with context modeling for image denoising , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).
[27] Eero P. Simoncelli. Modeling the joint statistics of images in the wavelet domain , 1999, Optics & Photonics.
[28] Martin J. Wainwright,et al. Adaptive Wiener denoising using a Gaussian scale mixture model in the wavelet domain , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).
[29] Jia Jie. Bayesian denoising of visual images in the wavelet domain , 2003 .
[30] David Mumford,et al. Statistics of natural images and models , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).
[31] Richard G. Baraniuk,et al. Wavelet statistical models and Besov spaces , 1999 .
[32] Xiang-Gen Xia,et al. Improved hidden Markov models in the wavelet-domain , 2001, IEEE Trans. Signal Process..
[33] Richard Baraniuk,et al. Multiscale texture segmentation using wavelet-domain hidden Markov models , 1998, Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284).
[34] I. Johnstone,et al. Ideal spatial adaptation by wavelet shrinkage , 1994 .
[35] Jian Liu,et al. Image denoising based on scale-space mixture modeling of wavelet coefficients , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).
[36] Nouna Kettaneh,et al. Statistical Modeling by Wavelets , 1999, Technometrics.
[37] N. Kingsbury. Complex Wavelets for Shift Invariant Analysis and Filtering of Signals , 2001 .
[38] Nick G. Kingsbury,et al. Hidden Markov tree modeling of complex wavelet transforms , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[39] B. Silverman,et al. Wavelet thresholding via a Bayesian approach , 1998 .
[40] David Mumford,et al. Statistics of range images , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[41] Eero P. Simoncelli. Statistical models for images: compression, restoration and synthesis , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).
[42] Kung Yao,et al. A representation theorem and its applications to spherically-invariant random processes , 1973, IEEE Trans. Inf. Theory.
[43] Michael T. Orchard,et al. Spatially adaptive image denoising under overcomplete expansion , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).
[44] D. Donoho,et al. Translation-Invariant De-Noising , 1995 .
[45] David Leporini,et al. Bayesian wavelet denoising: Besov priors and non-Gaussian noises , 2001, Signal Process..