Local Independent Factorization of Natural Scenes

In this paper, we study sparse representation of large-size natural scenes via local spatial dependency decomposition. We propose a local independent factorization model of natural scenes and develop a learning algorithm for adaptation of the synaptic weights. We investigate the dependency of neighboring location of the natural scene patches and derive learning algorithm to train the visual neural network. Some numerical experiments on natural scenes are performed to show the sparse representation of the visual sensory information.