Probabilistic framework for the adaptation and comparison of image codes

@inproceedings{Olshausen1999ProbabilisticFF,
title={Probabilistic framework for the adaptation and comparison of image codes},
author={Bruno A. Olshausen},
year={1999}
}

We apply a Bayesian method for inferring an optimal basis to the problem of finding efficient image codes for natural scenes. The basis functions learned by the algorithm are oriented and localized in both space and frequency, bearing a resemblance to two-dimensional Gabor functions, and increasing the number of basis functions results in a greater sampling density in position, orientation, and scale. These properties also resemble the spatial receptive fields of neurons in the primary visual… CONTINUE READING