Title :
A window-based Bayesian estimator for noise removal
Author :
Schultz, Richard R. ; Stevenson, Robert L.
Author_Institution :
Dept. of Electr. Eng., Notre Dame Univ., IN, USA
Abstract :
A window-based Bayesian restoration filter is proposed which smooths noise and preserves edges. The filter estimates a sample value by optimizing a partial signal likelihood function, dependent upon a set of surrounding elements. Simulations confirm that a noisy image restored by the window-based filter compares favorably to an estimate computed using the complete observed image, even for small window sizes
Keywords :
Bayes methods; filtering theory; image restoration; maximum likelihood estimation; noise; smoothing methods; edge preservation; image noise removal; noise smoothing; partial signal likelihood function; restoration filter; simulation; window-based Bayesian estimator; Bayesian methods; Computational modeling; Equations; Filters; Gaussian processes; Image reconstruction; Image restoration; Markov random fields; Nearest neighbor searches; Pixel; Signal restoration; Size control; Smoothing methods; Temperature;
Conference_Titel :
Circuits and Systems, 1994., Proceedings of the 37th Midwest Symposium on
Conference_Location :
Lafayette, LA
Print_ISBN :
0-7803-2428-5
DOI :
10.1109/MWSCAS.1994.518949
