The statistics of natural images
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[1] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.
[2] Claude E. Shannon,et al. Prediction and Entropy of Printed English , 1951 .
[3] E. Kretzmer. Statistics of television signals , 1952 .
[4] F. Attneave. Some informational aspects of visual perception. , 1954, Psychological review.
[5] L. Ryder,et al. Quantum Field Theory , 2001, Foundations of Modern Physics.
[6] Athanasios Papoulis,et al. Probability, Random Variables and Stochastic Processes , 1965 .
[7] D. G. Green,et al. Optical and retinal factors affecting visual resolution. , 1965, The Journal of physiology.
[8] F. Campbell,et al. Optical quality of the human eye , 1966, The Journal of physiology.
[9] L. Kadanoff. Scaling laws for Ising models near T(c) , 1966 .
[10] G. F. Cooper,et al. Development of the Brain depends on the Visual Environment , 1970, Nature.
[11] C. R. Carlson,et al. Image Descriptors for Displays , 1977 .
[12] A. Hughes. The Topography of Vision in Mammals of Contrasting Life Style: Comparative Optics and Retinal Organisation , 1977 .
[13] R. Voss,et al. ’’1/f noise’’ in music: Music from 1/f noise , 1978 .
[14] J. Lythgoe. The Ecology of vision , 1979 .
[15] S. Laughlin. A Simple Coding Procedure Enhances a Neuron's Information Capacity , 1981, Zeitschrift fur Naturforschung. Section C, Biosciences.
[16] J. Movshon,et al. Visual neural development. , 1981, Annual review of psychology.
[17] David R. Brillinger,et al. Time Series: Data Analysis and Theory. , 1982 .
[18] H. Barlow. What causes trichromacy? A theoretical analysis using comb-filtered spectra , 1982, Vision Research.
[19] 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.
[20] 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.
[21] K. Wilson. The renormalization group and critical phenomena , 1983 .
[22] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] I. Procaccia. Fractal structures in turbulence , 1984 .
[24] I. Ohzawa,et al. Contrast gain control in the cat's visual system. , 1985, Journal of neurophysiology.
[25] J. Cardy. Conformal invariance and critical behavior , 1986 .
[26] L. Maloney. Evaluation of linear models of surface spectral reflectance with small numbers of parameters. , 1986, Journal of the Optical Society of America. A, Optics and image science.
[27] J. Dowling. The Retina: An Approachable Part of the Brain , 1988 .
[28] G. J. Burton,et al. Color and spatial structure in natural scenes. , 1987, Applied optics.
[29] B. Frieden,et al. Image recovery: Theory and application , 1987, IEEE Journal of Quantum Electronics.
[30] 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.
[31] Heinz-Otto Peitgen,et al. The science of fractal images , 2011 .
[32] John G. Daugman,et al. Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..
[33] Arun N. Netravali,et al. Digital Pictures: Representation and Compression , 1988 .
[34] Stuart German,et al. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1988 .
[35] Terence D. Sanger,et al. Optimal unsupervised learning in a single-layer linear feedforward neural network , 1989, Neural Networks.
[36] Ralph Linsker,et al. How to Generate Ordered Maps by Maximizing the Mutual Information between Input and Output Signals , 1989, Neural Computation.
[37] Joseph J. Atick,et al. Towards a Theory of Early Visual Processing , 1990, Neural Computation.
[38] R Linsker,et al. Perceptual neural organization: some approaches based on network models and information theory. , 1990, Annual review of neuroscience.
[39] William Bialek,et al. Optimal Filtering in the Salamander Retina , 1990, NIPS.
[40] Reiner Lenz,et al. Group invariant pattern recognition , 1990, Pattern Recognit..
[41] M. Morrone,et al. Vision: Feature detection in biological and artificial visual systems , 1990 .
[42] W. Bialek,et al. Optimal Sampling of Natural Images: A Design Principle for the Visual System , 1990, NIPS 1990.
[43] Y. Gagne,et al. Velocity probability density functions of high Reynolds number turbulence , 1990 .
[44] K. Hsü,et al. Fractal geometry of music. , 1990, Proceedings of the National Academy of Sciences of the United States of America.
[45] C. Curcio,et al. Topography of ganglion cells in human retina , 1990, The Journal of comparative neurology.
[46] C. Webber,et al. Competitive learning, natural images and cortical cells , 1991 .
[47] John W. Woods,et al. Compound Gauss-Markov random fields for image estimation , 1991, IEEE Trans. Signal Process..
[48] Zhaoping Li,et al. Understanding Retinal Color Coding from First Principles , 1992, Neural Computation.
[49] J. Mollon,et al. The spatial arrangement of cones in the primate fovea , 1992, Nature.
[50] J. Dannemiller. Spectral reflectance of natural objects: how many basis functions are necessary? , 1992 .
[51] Leslie S. Smith,et al. The principal components of natural images , 1992 .
[52] C. Curcio,et al. Packing geometry of human cone photoreceptors: variation with eccentricity and evidence for local anisotropy. , 1992, Visual neuroscience.
[53] S. Laughlin. Retinal information capacity and the function of the pupil , 1992, Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians.
[54] William Bialek,et al. Seeing Beyond the Nyquist Limit , 1999, Neural Computation.
[55] Joseph J. Atick,et al. What Does the Retina Know about Natural Scenes? , 1992, Neural Computation.
[56] D. Heeger. Normalization of cell responses in cat striate cortex , 1992, Visual Neuroscience.
[57] D. Tolhurst,et al. Amplitude spectra of natural images , 1992 .
[58] S. Laughlin. Information capacity and the function of the human pupil , 1992 .
[59] J. Nadal,et al. Optimal unsupervised learning , 1994 .
[60] William Bialek,et al. Statistics of Natural Images: Scaling in the Woods , 1993, NIPS.
[61] R. Webster. Ambient noise statistics , 1993, IEEE Trans. Signal Process..
[62] Robert J. Safranek,et al. Signal compression based on models of human perception , 1993, Proc. IEEE.
[63] Fred Rieke,et al. Coding Efficiency and Information Rates in Sensory Neurons , 1993 .
[64] A. Jacquin. Fractal image coding: a review , 1993, Proc. IEEE.
[65] Zhaoping Li,et al. Toward a Theory of the Striate Cortex , 1994, Neural Computation.
[66] S. Laughlin. Matching coding, circuits, cells, and molecules to signals: General principles of retinal design in the fly's eye , 1994, Progress in Retinal and Eye Research.
[67] T. K. Truong,et al. Comparison of international standards for lossless still image compression , 1994, Proc. IEEE.
[68] Zhaoping Li,et al. Efficient stereo coding in the multiscale representation , 1994 .
[69] Daniel L. Ruderman,et al. Designing receptive fields for highest fidelity , 1994 .
[70] W. Ebeling,et al. Entropy and Long-Range Correlations in Literary English , 1993, cond-mat/0204108.
[71] Ralph Linsker,et al. Sensory Processing and Information Theory , 1994 .
[72] David J. Field,et al. What Is the Goal of Sensory Coding? , 1994, Neural Computation.