Function Regression for Image Restoration by Fuzzy Hough Transform

Koichiro KUBO  Kiichi URAHAMA 

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences  Vol.E81-A  No.6  pp.1305-1309
Publication Date: 1998/06/20
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Nonlinear Problems
Keyword: 
function approximation,  fuzzy Hough transform,  image restoration, 

Full Text: PDF(336KB)

Summary: 
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 distribution is assumed to take a robust form and its local maxima are extracted to yield restored images. This statistical scheme is implemented by a feedforward neural network composed of radial basis function neurons and a local winner-takes-all subnetwork.