Image denoising using multiple wavelet representations and local contextual hidden Markov model
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[1] Xiang-Gen Xia,et al. Wavelet-Based Statistical Image Processing Using Hidden Markov Tree Model , 2000 .
[2] Michael T. Orchard,et al. Spatially adaptive image denoising under overcomplete expansion , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).
[3] Michael Elad,et al. A generalized uncertainty principle and sparse representation in pairs of bases , 2002, IEEE Trans. Inf. Theory.
[4] Mário A. T. Figueiredo. Adaptive Sparseness for Supervised Learning , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[5] I. Selesnick,et al. Bivariate shrinkage with local variance estimation , 2002, IEEE Signal Processing Letters.
[6] Guoliang Fan,et al. Image denoising using a local contextual hidden Markov model in the wavelet domain , 2001, IEEE Signal Processing Letters.
[7] Martin J. Wainwright,et al. Image denoising using scale mixtures of Gaussians in the wavelet domain , 2003, IEEE Trans. Image Process..
[8] 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.
[9] R.G. Baraniuk,et al. Contextual hidden Markov models for wavelet-domain signal processing , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).
[10] Guang Deng,et al. A signal denoising algorithm based on overcomplete wavelet representations and Gaussian models , 2007, Signal Process..
[11] Justin K. Romberg,et al. Bayesian tree-structured image modeling using wavelet-domain hidden Markov models , 2001, IEEE Trans. Image Process..