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Issue No.04 - July (1988 vol.10)
pp: 452-468
ABSTRACT
<p>A scheme suitable for visual information representation in a combined frequency-position space is investigated through image decomposition into a finite set of two-dimensional Gabor elementary functions (GEF). The scheme is generalized to account for the position-dependent Gabor-sampling rate, oversampling, logarithmic frequency scaling and phase-quantization characteristic of the visual system. Comparison of reconstructed signal highlights the advantages of the generalized Gabor scheme in coding typical bandlimited images. It is shown that there exists a tradeoff between the number of frequency components used per position and the number of such clusters (sampling rate) utilized along the spatial coordinate.</p>
INDEX TERMS
biological vision; 2D Gabor elementary functions; picture processing; pattern recognition; Gabor scheme; image representation; machine vision; frequency-position space; image decomposition; frequency scaling; phase-quantization; coding; clusters; sampling; pattern recognition; picture processing
CITATION
M. Porat, Y.Y. Zeevi, "The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.10, no. 4, pp. 452-468, July 1988, doi:10.1109/34.3910
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