Sparse coding of natural contours

Abstract

An important approach in visual neuroscience considers how the function of the early visual system relates to the statistics of its natural input. Previous work has shown how the classical receptive fields and the organization (topography) of the primary visual cortex can be viewed as efficient coding of natural images. Here, we extend the framework by considering how the responses of complex cells could be efficiently coded by a higher-order neural layer. This leads to the sparse coding of contours in natural images, and can explain certain extra-classical properties of receptive fields.