Issue No. 04 - July (1988 vol. 10)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.3910
<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>
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
Y. Zeevi and M. Porat, "The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 10, no. , pp. 452-468, 1988.