1 THE BRAIN’S VIEW OF THE NATURAL WORLD IN MOTION: COMPUTING STRUCTURE FROM FUNCTION USING DIRECTIONAL FOURIER TRANSFORMATIONS

Attractive possibilities exist for the brain to solve important problems of visual process-ing in Fourier space. First, we describe a wave-interference model for computing motion contrast directly from the moving intensity distribution, without the need for direction-ally selective motion sensors. We then propose a global method for motion-based image segmentation based on unsupervised clustering in a three-dimensional Fourier space. The Fourier components of coherently moving entities are segregated from the remainder by means of a simple velocity proximity measure. This is accomplished without altering the spatial frequency components encoding the object, thereby ensuring that the spatiotem-poral features of the segregated object can be reconstructed