Function Regression for Image Restoration by Fuzzy Hough Transform

摘要

A function approximation scheme for image restoration is presented to resolve conflicting demands for smoothing within each object and differentiation between objects. Images are defined by probability distributions in the augmented functional space composed of image values and image planes. According to the fuzzy Hough transform, the probability distri- bution is assumed to take a robust form and its local maxima are extracted to yield restored images. This statistical scheme is im- plemented by a feedforward neural network composed of radial basis function neurons and a local winner-takes-all subnetwork.