RECONSTRUCTION AND BOUNDARY DETECTION OF RANGE AND INTENSITY IMAGES USING MULTISCALE MRF REPRESENTATIONS

The basic difficulty encountered in filtering-based multiscale boundar y detection methods is the elimination of noise and insignificant edge s without distorting the shape of boundaries, These methods remove noi se and unnecessary detail by blurring the input image at different sca les, which results in the loss of positional accuracy at the image dis continuities. In this paper, a nonlinear multiscale boundary detection method which prevents the conflict between the detection and localiza tion goals is introduced. The method uses multiscale representations o f coupled Markov random fields and applies a stochastic regularization scheme based on the Bayesian approach, This allows the robust integra tion of boundary information extracted at multiple scales simultaneous ly. The scheme is applicable to intensity and range images as well as to sparse data and eliminates the dependency on edge operator size whi ch is the main difficulty in filtering-based multiscale techniques. (C ) 1996 Academic Press, Inc.