Natural image statistics and visual processing

The visual system of a human or animal that functions in its natural environment receives huge amounts of visual information. This information is vital for the survival of the organism. In this thesis I follow the hypothesis that evolution has optimised the biological visual system to process the images that it commonly encounters i.e., natural images. To this end I investigate the structure of natural images with statistical methods, with as the ultimate aim to gain a better understanding of the visual processing in biological systems. ... Zie: Summary.

[1]  R. L. Valois,et al.  The orientation and direction selectivity of cells in macaque visual cortex , 1982, Vision Research.

[2]  RussLL L. Ds Vnlos,et al.  SPATIAL FREQUENCY SELECTIVITY OF CELLS IN MACAQUE VISUAL CORTEX , 2022 .

[3]  D C Van Essen,et al.  Information processing in the primate visual system: an integrated systems perspective. , 1992, Science.

[4]  George Francis Harpur,et al.  Low Entropy Coding with Unsupervised Neural Networks , 1997 .

[5]  D. Tolhurst,et al.  Amplitude spectra of natural images. , 1992, Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians.

[6]  J. V. van Hateren.  Spatial, temporal and spectral pre-processing for colour vision , 1993, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[7]  S. Laughlin,et al.  Matching Coding to Scenes to Enhance Efficiency , 1983 .

[8]  J. Daugman.  Two-dimensional spectral analysis of cortical receptive field profiles , 1980, Vision Research.

[9]  F. Harris.  On the use of windows for harmonic analysis with the discrete Fourier transform , 1978, Proceedings of the IEEE.

[10]  J. Atick,et al.  STATISTICS OF NATURAL TIME-VARYING IMAGES , 1995 .

[11]  Ralph Linsker,et al.  Deriving Receptive Fields Using an Optimal Encoding Criterion , 1992, NIPS.

[12]  Joseph J. Atick,et al.  Towards a Theory of Early Visual Processing , 1990, Neural Computation.

[13]  Terrence J. Sejnowski,et al.  The “independent components” of natural scenes are edge filters , 1997, Vision Research.

[14]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[15]  D. Heeger.  Normalization of cell responses in cat striate cortex , 1992, Visual Neuroscience.

[16]  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.

[17]  R C Reid,et al.  Efficient Coding of Natural Scenes in the Lateral Geniculate Nucleus: Experimental Test of a Computational Theory , 1996, The Journal of Neuroscience.

[18]  John Daugman,et al.  Quadrature-phase simple-cell pairs are appropriately described in complex analytic form , 1993 .

[19]  Michael J. Berry,et al.  Adaptation of retinal processing to image contrast and spatial scale , 1997, Nature.

[20]  Victor A. F. Lamme,et al.  Contextual Modulation in Primary Visual Cortex , 1996, The Journal of Neuroscience.

[21]  D. Chakrabarti,et al.  A fast fixed - point algorithm for independent component analysis , 1997 .

[22]  Trichur Raman Vidyasagar,et al.  A linear model fails to predict orientation selectivity of cells in the cat visual cortex. , 1996, The Journal of physiology.

[23]  D. Field,et al.  The structure and symmetry of simple-cell receptive-field profiles in the cat’s visual cortex , 1986, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[24]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

[25]  Heinz-Otto Peitgen,et al.  The science of fractal images , 2011 .

[26]  K. Clayton,et al.  The perception of natural contour. , 1993, Psychological review.

[27]  Joseph J. Atick,et al.  What Does the Retina Know about Natural Scenes? , 1992, Neural Computation.

[28]  D. A. Burkhardt,et al.  Light adaptation and photopigment bleaching in cone photoreceptors in situ in the retina of the turtle , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[29]  S. Laughlin.  A Simple Coding Procedure Enhances a Neuron's Information Capacity , 1981, Zeitschrift fur Naturforschung. Section C, Biosciences.

[30]  Leslie S. Smith,et al.  The principal components of natural images , 1992 .

[31]  P. Lennie,et al.  Contrast adaptation in striate cortex of macaque , 1989, Vision Research.

[32]  J. H. van Hateren,et al.  Temporal properties of natural scenes , 1996, Human Vision and Electronic Imaging.

[33]  Erkki Oja,et al.  One-unit Learning Rules for Independent Component Analysis , 1996, NIPS.

[34]  D. Tolhurst,et al.  Discrimination of changes in the second-order statistics of natural and synthetic images , 1994, Vision Research.

[35]  N. Jeremy Usdin,et al.  Discrete Simulation of Colored Noise and Stochastic Processes and llf" Power Law Noise Generation , 1995 .

[36]  Erkki Oja,et al.  Image Feature Extraction Using Independent Component Analysis , 1996 .

[37]  R. Baddeley,et al.  Searching for filters with 'interesting' output distributions: an uninteresting direction to explore? , 1996, Network.

[38]  J. V. van Hateren,et al.  Independent component filters of natural images compared with simple cells in primary visual cortex , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[39]  J. V. van Hateren,et al.  Spatiotemporal contrast sensitivity of early vision , 1993, Vision Research.

[40]  W. Bialek,et al.  Optimal Sampling of Natural Images: A Design Principle for the Visual System , 1990, NIPS 1990.

[41]  D. Ruderman.  The statistics of natural images , 1994 .

[42]  J. H. van Hateren,et al.  Modelling the Power Spectra of Natural Images: Statistics and Information , 1996, Vision Research.

[43]  Zhaoping Li,et al.  Towards a theory of striate cortex , 1994 .

[44]  V. Hateren,et al.  Processing of natural time series of intensities by the visual system of the blowfly , 1997, Vision Research.

[45]  G. J. Burton,et al.  Color and spatial structure in natural scenes. , 1987, Applied optics.

[46]  William Bialek,et al.  Statistics of Natural Images: Scaling in the Woods , 1993, NIPS.

[47]  Bruno A. Olshausen,et al.  Inferring Sparse, Overcomplete Image Codes Using an Efficient Coding Framework , 1998, NIPS.

[48]  E. Peli.  Contrast in complex images. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[49]  David J. Field,et al.  Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.

[50]  Horace Barlow,et al.  What is the computational goal of the neocortex , 1994 .

[51]  A. Parker,et al.  Two-dimensional spatial structure of receptive fields in monkey striate cortex. , 1988, Journal of the Optical Society of America. A, Optics and image science.

[52]  J. Atick,et al.  Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus , 1995 .

[53]  Aapo Hyvärinen,et al.  A family of fixed-point algorithms for independent component analysis , 1997, ICASSP.

[54]  D. Hubel,et al.  Receptive fields and functional architecture of monkey striate cortex , 1968, The Journal of physiology.

[55]  Jarmo Hurri,et al.  Independent Component Analysis of Image Data , 1997 .

[56]  F. Attneave.  Some informational aspects of visual perception. , 1954, Psychological review.

[57]  S Marcelja,et al.  Mathematical description of the responses of simple cortical cells. , 1980, Journal of the Optical Society of America.

[58]  Daniel L. Ruderman,et al.  Origins of scaling in natural images , 1996, Vision Research.

[59]  Jeffrey A. Sloan,et al.  Spatial frequency analysis of the visual environment: Anisotropy and the carpentered environment hypothesis , 1978, Vision Research.

[60]  Terrence J. Sejnowski,et al.  Edges are the Independent Components of Natural Scenes , 1996, NIPS.

[61]  W A Richards,et al.  Lightness scale from image intensity distributions. , 1981, Applied optics.

[62]  Leon Lagnado,et al.  Signal flow in visual transduction , 1992, Neuron.

[63]  J.G. Daugman,et al.  Entropy reduction and decorrelation in visual coding by oriented neural receptive fields , 1989, IEEE Transactions on Biomedical Engineering.

[64]  Peter Lennie,et al.  SPATIAL FREQUENCY ANALYSIS IN THE VISUAL , 1985 .

[65]  J. V. van Hateren,et al.  Real and optimal neural images in early vision , 1992, Nature.

[66]  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.