Paper Info
Title
Image representation using 2D Gabor wavelets
Abstract
This paper extends to two dimensions the frame criterion developed by Daubechies for one-dimensional wavelets, and it computes the frame bounds for the particular case of 2D Gabor wavelets. Completeness criteria for 2D Gabor image representations are important because of their increasing role in many computer vision applications and also in modeling biological vision, since recent neurophysiological evidence from the visual cortex of mammalian brains suggests that the filter response profiles of the main class of linearly-responding cortical neurons (called simple cells) are best modeled as a family of self-similar 2D Gabor wavelets. We therefore derive the conditions under which a set of continuous 2D Gabor wavelets will provide a complete representation of any image, and we also find self-similar wavelet parametrization which allow stable reconstruction by summation as though the wavelets formed an orthonormal basis. Approximating a “tight frame” generates redundancy which allows low-resolution neural responses to represent high-resolution images
Year
DOI
Venue
1996
10.1109/34.541406
IEEE Trans. Pattern Anal. Mach. Intell.
Keywords
Field
DocType
frame bound,image representation,image coding,2d gabor wavelets,neurophysiology,wavelet transforms,biological vision,frame bounds,coarse coding,visual cortex,gabor coefficient,image reconstruction,computer vision application,tight frame,computer vision,frame criterion,gabor wavelet,gabor wavelets,high-resolution image,gabor image representation,self-similar wavelet parametrization,application software,two dimensions
Gabor–Wigner transform,Computer vision,Pattern recognition,Computer science,Gabor wavelet,Multi-scale approaches,Legendre wavelet,Orthonormal basis,Artificial intelligence,Gabor transform,Wavelet transform,Wavelet
Journal
Volume
Issue
ISSN
18
10
0162-8828
Citations 
PageRank 
References 
616
56.56
8
Authors
1
Search Limit
100616
Name
Order
Citations
PageRank
Tai Sing Lee179488.73