期刊
NETWORK-COMPUTATION IN NEURAL SYSTEMS
卷 17, 期 1, 页码 85-102出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/09548980500439602
关键词
human vision; natural image statistics; ICA; wavelets; non-linear systems; incremental thresholds; gain control; divisive normalization
It has been argued that the aim of non-linearities in different visual and auditory mechanisms may be to remove the relations between the coefficients of the signal after global linear ICA-like stages. Specifically, in Schwartz and Simoncelli (2001), it was shown that masking effects are reproduced by fitting the parameters of a particular non-linearity in order to remove the dependencies between the energy of wavelet coefficients. In this work, we present a different result that supports the same efficient encoding hypothesis. However, this result is more general because, instead of assuming any specific functional form for the non-linearity we show that by using an unconstrained approach, masking-like behavior emerges directly from natural images. This result is an additional indication that Barlow's efficient encoding hypothesis may explain not only the shape of receptive fields of VI sensors but also their non-linear behavior.
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