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M. Porat, Y.Y. Zeevi, "The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, no. 4, pp. 452468, July, 1988.  
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@article{ 10.1109/34.3910, author = {M. Porat and Y.Y. Zeevi}, title = {The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {10}, number = {4}, issn = {01628828}, year = {1988}, pages = {452468}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.3910}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision IS  4 SN  01628828 SP452 EP468 EPD  452468 A1  M. Porat, A1  Y.Y. Zeevi, PY  1988 KW  biological vision; 2D Gabor elementary functions; picture processing; pattern recognition; Gabor scheme; image representation; machine vision; frequencyposition space; image decomposition; frequency scaling; phasequantization; coding; clusters; sampling; pattern recognition; picture processing VL  10 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
A scheme suitable for visual information representation in a combined frequencyposition space is investigated through image decomposition into a finite set of twodimensional Gabor elementary functions (GEF). The scheme is generalized to account for the positiondependent Gaborsampling rate, oversampling, logarithmic frequency scaling and phasequantization 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.
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