Natural scene statistics at the centre of gaze.

Early stages of visual processing may exploit the characteristic structure of natural visual stimuli. This structure may differ from the intrinsic structure of natural scenes, because sampling of the environment is an active process. For example, humans move their eyes several times a second when looking at a scene. The portions of a scene that fall on the fovea are sampled at high spatial resolution, and receive a disproportionate fraction of cortical processing. We recorded the eye positions of human subjects while they viewed images of natural scenes. We report that active selection affected the statistics of the stimuli encountered by the fovea, and also by the parafovea up to eccentricities of 4 degrees. We found two related effects. First, subjects looked at image regions that had high spatial contrast. Second, in these regions, the intensities of nearby image points (pixels) were less correlated with each other than in images selected at random. These effects could serve to increase the information available to the visual system for further processing. We show that both of these effects can be simply obtained by constructing an artificial ensemble comprised of the highest-contrast regions of images.

[1]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

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

[3]  N. Mackworth,et al.  The gaze selects informative details within pictures , 1967 .

[4]  A. L. I︠A︡rbus.  Eye Movements and Vision , 1967 .

[5]  A. L. Yarbus,et al.  Eye Movements and Vision , 1967, Springer US.

[6]  N. Mackworth,et al.  Cognitive determinants of fixation location during picture viewing. , 1978, Journal of experimental psychology. Human perception and performance.

[7]  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.

[8]  M. Lévesque.  Perception , 1986, The Yale Journal of Biology and Medicine.

[9]  K. Rayner,et al.  Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity , 1986, Memory & cognition.

[10]  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.

[11]  William Bialek,et al.  Coding and computation with neural spike trains , 1990 .

[12]  D. Tolhurst,et al.  Amplitude spectra of natural images , 1992 .

[13]  M P Eckert,et al.  Efficient coding of natural time varying images in the early visual system. , 1993, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

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

[15]  C. C. Law,et al.  Formation of receptive fields in realistic visual environments according to the Bienenstock, Cooper, and Munro (BCM) theory. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[16]  David J. Field,et al.  What Is the Goal of Sensory Coding? , 1994, Neural Computation.

[17]  D. Field,et al.  What's constant in contrast constancy? The effects of scaling on the perceived contrast of bandpass patterns , 1995, Vision Research.

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

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

[20]  S. Laughlin,et al.  Insect motion detectors matched to visual ecology , 1996, Nature.

[21]  Zhaoping Li,et al.  A Theory of the Visual Motion Coding in the Primary Visual Cortex , 1996, Neural Computation.

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

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

[24]  N Brady,et al.  Spatial Scale Interactions and Image Statistics , 1997, Perception.

[25]  Leon N. Cooper,et al.  BCM network develops orientation selectivity and ocular dominance in natural scene environment , 1997, Vision Research.

[26]  D. S. Wooding,et al.  Fixation Patterns Made during Brief Examination of Two-Dimensional Images , 1997, Perception.

[27]  S. Laughlin,et al.  Spatio-temporal properties of motion detectors matched to low image velocities in hovering insects , 1997, Vision Research.

[28]  D. Tolhurst,et al.  Band-limited contrast in natural images explains the detectability of changes in the amplitude spectra , 1997, Vision Research.

[29]  S. Yantis,et al.  Visual attention: control, representation, and time course. , 1997, Annual review of psychology.

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

[31]  J. H. Hateren,et al.  Independent component filters of natural images compared with simple cells in primary visual cortex , 1998 .

[32]  Nathan Intrator,et al.  Receptive Field Formation in Natural Scene Environments: Comparison of Single-Cell Learning Rules , 1997, Neural Computation.

[33]  Claude E. Shannon,et al.  A mathematical theory of communication , 1948, MOCO.