A signal denoising algorithm based on overcomplete wavelet representations and Gaussian models
暂无分享,去创建一个
[1] Steve McLaughlin,et al. Comparative study of textural analysis techniques to characterise tissue from intravascular ultrasound , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.
[2] D. Madigan,et al. Bayesian Model Averaging for Linear Regression Models , 1997 .
[3] K. Jarrod Millman,et al. Learning Sparse Codes with a Mixture-of-Gaussians Prior , 1999, NIPS.
[4] Benjamin Belzer,et al. Wavelet filter evaluation for image compression , 1995, IEEE Trans. Image Process..
[5] Pierre Moulin,et al. Multiple-domain image modeling and restoration , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).
[6] Michael Elad,et al. Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[7] Robert D. Nowak,et al. Wavelet-based statistical signal processing using hidden Markov models , 1998, IEEE Trans. Signal Process..
[8] Pierre Moulin,et al. Analysis of Multiresolution Image Denoising Schemes Using Generalized Gaussian and Complexity Priors , 1999, IEEE Trans. Inf. Theory.
[9] Simon Haykin,et al. Image Denoising by Sparse Code Shrinkage , 2001 .
[10] Levent Sendur,et al. Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency , 2002, IEEE Trans. Signal Process..
[11] Kannan Ramchandran,et al. Low-complexity image denoising based on statistical modeling of wavelet coefficients , 1999, IEEE Signal Processing Letters.
[12] P. J. Green,et al. Density Estimation for Statistics and Data Analysis , 1987 .
[13] Jong-Sen Lee,et al. Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Martin Vetterli,et al. Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..
[15] Jianqing Fan,et al. Regularization of Wavelet Approximations , 2001 .
[16] David J. C. MacKay,et al. Bayesian Interpolation , 1992, Neural Computation.
[17] Simon Haykin,et al. Intelligent Signal Processing , 2001 .
[18] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[19] Michael Elad,et al. A generalized uncertainty principle and sparse representation in pairs of bases , 2002, IEEE Trans. Inf. Theory.
[20] Guang Deng. Signal estimation using multiple-wavelet representations and Gaussian models , 2005, IEEE International Conference on Image Processing 2005.
[21] José M. Bioucas-Dias,et al. Bayesian wavelet-based image deconvolution: a GEM algorithm exploiting a class of heavy-tailed priors , 2006, IEEE Transactions on Image Processing.
[22] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[23] Yan Yang,et al. Image Denoising by Sparse Code Shrinkage , 2009, 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing.
[24] Martin J. Wainwright,et al. Image denoising using scale mixtures of Gaussians in the wavelet domain , 2003, IEEE Trans. Image Process..
[25] Michael T. Orchard,et al. Spatially adaptive image denoising under overcomplete expansion , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).
[26] I. Selesnick,et al. Bivariate shrinkage with local variance estimation , 2002, IEEE Signal Processing Letters.
[27] Mário A. T. Figueiredo. Adaptive Sparseness for Supervised Learning , 2003, IEEE Trans. Pattern Anal. Mach. Intell..