Lower bounds on the redundancy of natural images
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[1] Yuhong Yang. Elements of Information Theory (2nd ed.). Thomas M. Cover and Joy A. Thomas , 2008 .
[2] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[3] Eero P. Simoncelli,et al. Natural signal statistics and sensory gain control , 2001, Nature Neuroscience.
[4] Eero P. Simoncelli,et al. Reducing statistical dependencies in natural signals using radial Gaussianization , 2008, NIPS.
[5] J. Bernardo. Expected Information as Expected Utility , 1979 .
[6] Terrence J. Sejnowski,et al. Learning Overcomplete Representations , 2000, Neural Computation.
[7] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[8] Martin J. Wainwright,et al. Scale Mixtures of Gaussians and the Statistics of Natural Images , 1999, NIPS.
[9] M. Bethge. Factorial coding of natural images: how effective are linear models in removing higher-order dependencies? , 2006, Journal of the Optical Society of America. A, Optics, image science, and vision.
[10] Matthias Bethge,et al. The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction , 2008, NIPS.
[11] Hans Föllmer,et al. On entropy and information gain in random fields , 1973 .
[12] Liam Paninski,et al. Estimation of Entropy and Mutual Information , 2003, Neural Computation.
[13] Y. Petrov,et al. Local correlations, information redundancy, and sufficient pixel depth in natural images. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.
[14] Matthias Bethge,et al. Natural Image Coding in V1: How Much Use Is Orientation Selectivity? , 2008, PLoS Comput. Biol..
[15] R. Jennrich,et al. Acceleration of the EM Algorithm by using Quasi‐Newton Methods , 1997 .
[16] William F. Schreiber,et al. The measurement of third order probability distributions of television signals , 1956, IRE Trans. Inf. Theory.
[17] G. Buchsbaum,et al. Trichromacy, opponent colours coding and optimum colour information transmission in the retina , 1983, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[18] Joseph J. Atick,et al. What Does the Retina Know about Natural Scenes? , 1992, Neural Computation.
[19] Albert Perez. Ε-admissible Simplifications of the Dependence Structure of a Set of Random Variables , 1977, Kybernetika.
[20] T. W. Lee,et al. Chromatic structure of natural scenes. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.
[21] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[22] D. W. Scott. On optimal and data based histograms , 1979 .
[23] William Bialek,et al. Statistics of Natural Images: Scaling in the Woods , 1993, NIPS.
[24] Michael S. Lewicki,et al. Emergence of complex cell properties by learning to generalize in natural scenes , 2009, Nature.
[25] S. Laughlin,et al. Predictive coding: a fresh view of inhibition in the retina , 1982, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[26] Alex Pentland,et al. Discriminative, generative and imitative learning , 2002 .
[27] D. Field,et al. Estimates of the information content and dimensionality of natural scenes from proximity distributions. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.
[28] T. Sejnowski,et al. Color opponency is an efficient representation of spectral properties in natural scenes , 2002, Vision Research.
[29] J. H. Hateren,et al. Independent component filters of natural images compared with simple cells in primary visual cortex , 1998 .
[30] Leonhard Held,et al. Gaussian Markov Random Fields: Theory and Applications , 2005 .
[31] Bruno A. Olshausen,et al. PROBABILISTIC FRAMEWORK FOR THE ADAPTATION AND COMPARISON OF IMAGE CODES , 1999 .
[32] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[33] R Linsker,et al. Perceptual neural organization: some approaches based on network models and information theory. , 1990, Annual review of neuroscience.