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Issue No.05 - May (2006 vol.28)
pp: 822-826
ABSTRACT
This paper investigates the principal components (PCs) of natural gray and color images. A horizontal and vertical typology of PCs is found which leads to the identification of groups of basis functions for steerable bandpass filters. Using this system, the contribution of spatio-chromatic structure to the total variance can be quantified for selected spatial frequencies.
INDEX TERMS
Statistical image representation, feature measurement, feature representation, texture, color scene analysis, shape, computer vision, computational models of vision, connectionism and neural nets.
CITATION
Gunther Heidemann, "The Principal Components of Natural Images Revisited", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.28, no. 5, pp. 822-826, May 2006, doi:10.1109/TPAMI.2006.107
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