Factorial coding of natural images: How effective are linear filters in removing higher-order dependencies?


Our todays understanding of how neurons in the early visual system respond to the light intensity patterns on the retina can be described basically in terms of firing rates and linear filtering (plus pointwise nonlinearities). It has been suggested that the purpose of this filtering is to represent the retinal image by the activition pattern of statistically less dependent features (ie redundancy reduction). In particular, the filters found with independent component analysis (ICA) for natural images resemble important properties of simple cells in striate cortex: they are localized, oriented, and bandpass.