A low-level cortical perception model with applications to image analysis

We describe a mathematical model of low-level biological vision based on two recent neurophysiological findings regarding rapid adaptation and response in primate striate cortex (cortical visual area V1) to similarities in the structure of viewed images. We describe the experimental findings to make clear the basis for the model. The proposed algorithm uses independent component analysis (ICA) decompositions to find a structure across a series of visual inputs. The performance of the algorithm is illustrated on a problem involving detection of changes in satellite imagery. Its image discrimination capabilities are shown to be superior to those of a conventional structure finding method used in image processing