Wavelet for binocular vision modeling

In the present study, binocular vision properties were modeled using a single elementary wavelet. Opponent responses (ON-OFF) appeared in the first stages of the neural coding in the retina. This property was assumed to build an adequate wavelet showing a positive part (On) and a negative part (OFF). We have examined the experimental orientation and position disparity given by Bishop. We assumed that the theoretical position disparity was given by a combination of two wavelets for a given orientation disparity β. A change in β implied a change in the magnitude of one of the wavelets and consequently a change in the wavelets combination. There was a close match between the theoretical and experimental position disparity curves according to the changes in orientation disparity.

[1]  Osvaldo A. Rosso,et al.  Wavelet entropy in event-related potentials: a new method shows ordering of EEG oscillations , 2001, Biological Cybernetics.

[2]  Stéphane Mallat,et al.  Multifrequency channel decompositions of images and wavelet models , 1989, IEEE Trans. Acoust. Speech Signal Process..

[3]  Zhaoping Li,et al.  Efficient stereo coding in the multiscale representation , 1994 .

[4]  Leo Maurice Hurvich,et al.  Color vision , 1981 .

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

[6]  D G Stork,et al.  Do Gabor functions provide appropriate descriptions of visual cortical receptive fields? , 1990, Journal of the Optical Society of America. A, Optics and image science.

[7]  G. A Theory for Multiresolution Signal Decomposition : The Wavelet Representation , 2004 .

[8]  R. L. Valois,et al.  A multi-stage color model , 1993, Vision Research.

[9]  April Khademi,et al.  Shift-invariant discrete wavelet transform analysis for retinal image classification , 2007, Medical & Biological Engineering & Computing.

[10]  Ji-Jie Pang,et al.  Relative contributions of bipolar cell and amacrine cell inputs to light responses of ON, OFF and ON–OFF retinal ganglion cells , 2002, Vision Research.

[11]  Karen K. De Valois,et al.  On “A three-stage color model” , 1996, Vision Research.

[12]  Behzad Mansouri,et al.  Integration, segregation, and binocular combination. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.

[13]  V. Billock The relationship between simple and double opponent cells , 1991, Vision Research.

[14]  Barry B. Lee,et al.  Center surround receptive field structure of cone bipolar cells in primate retina , 2000, Vision Research.

[15]  C. Zetzsche,et al.  Nonlinear and extra-classical receptive field properties and the statistics of natural scenes , 2001, Network.

[16]  D. Ts'o,et al.  The organization of chromatic and spatial interactions in the primate striate cortex , 1988, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[17]  Orientation and Position Disparities in Stereopsis , 1978 .

[18]  B. B. Lee,et al.  Receptive field structure in the primate retina , 1996, Vision Research.

[19]  J. Daugman Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[20]  L. Croner,et al.  Receptive fields of P and M ganglion cells across the primate retina , 1995, Vision Research.

[21]  H. Kolb,et al.  Anatomical pathways for color vision in the human retina , 1991, Visual Neuroscience.

[22]  Donald C. Stockbarger,et al.  An Incandescent Lamp with a Quartz Window , 1924 .

[23]  Fan Gao,et al.  Functional Architecture of Synapses in the Inner Retina: Segregation of Visual Signals by Stratification of Bipolar Cell Axon Terminals , 2000, The Journal of Neuroscience.

[24]  Andrew P. Bradley,et al.  A wavelet visible difference predictor , 1999, IEEE Trans. Image Process..

[25]  N Jeremy Hill,et al.  Cue combination and the effect of horizontal disparity and perspective on stereoacuity. , 2007, Spatial vision.

[26]  E. Serrano,et al.  Analysis of wavelet-filtered tonic-clonic electroencephalogram recordings , 2004, Medical and Biological Engineering and Computing.

[27]  J. Mollon Color vision. , 1982, Annual review of psychology.

[28]  L Gaudart,et al.  Wavelet transform in human visual channels. , 1993, Applied optics.

[29]  P. E. Tikkanen,et al.  Nonlinear wavelet and wavelet packet denoising of electrocardiogram signal , 1999, Biological Cybernetics.

[30]  Jian Yang,et al.  Do Gabor functions provide appropriate descriptions of visual cortical receptive fields?: comment , 1992 .

[31]  C. Enroth-Cugell,et al.  The contrast sensitivity of retinal ganglion cells of the cat , 1966, The Journal of physiology.

[32]  S. L. Guth Comments on “A multi-stage color model” , 1996, Vision Research.

[33]  P. O. Bishop,et al.  Theory of spatial position and spatial frequency relations in the receptive fields of simple cells in the visual cortex , 1982, Biological Cybernetics.

[34]  Amara Lynn Graps,et al.  An introduction to wavelets , 1995 .

[35]  S A Klein,et al.  Minimizing and maximizing the joint space-spatial frequency uncertainty of Gabor-like functions: comment. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[36]  Marie-Françoise Lucas,et al.  Optimal wavelets for biomedical signal compression , 2006, Medical and Biological Engineering and Computing.

[37]  Thérèse Collins,et al.  Eye movement signals influence perception: Evidence from the adaptation of reactive and volitional saccades , 2006, Vision Research.

[38]  S L Guth,et al.  Model for color vision and light adaptation. , 1991, Journal of the Optical Society of America. A, Optics and image science.

[39]  Thérèse Collins,et al.  The use of recurrent signals about adaptation for subsequent saccade programming depends on object structure , 2006, Brain Research.

[40]  R. W. Rodieck Quantitative analysis of cat retinal ganglion cell response to visual stimuli. , 1965, Vision research.

[41]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..