Title :
Fuzzy image smoothing
Author_Institution :
Intell. Autom. Lab., Heriot-Watt Univ., Edinburgh, UK
Abstract :
A fuzzy model for a noisy image sequence is given, and the possibility distribution function for an estimate of the original image is deduced. An optimal estimate criterion, called the maximum possibility criterion, is presented, and the fuzzy image smoothing algorithm is derived. This algorithm can be realized by a simple digital structure with the desirable property of reduced memory requirements. For the average relative error, the algorithm performs better than the conventional average of multiple images algorithm with the distinct advantage of suppressing noise in the case of a small number of images
Keywords :
filtering and prediction theory; fuzzy set theory; minimisation; picture processing; fuzzy image smoothing algorithm; maximum possibility criterion; noise suppression; noisy image sequence; optimal estimate criterion; possibility distribution function; reduced memory requirements; Automation; Digital images; Distribution functions; Filters; Image processing; Image sequences; Noise reduction; Pixel; Smoothing methods; Uncertainty;
Conference_Titel :
Pattern Recognition, 1990. Proceedings., 10th International Conference on
Conference_Location :
Atlantic City, NJ
Print_ISBN :
0-8186-2062-5
DOI :
10.1109/ICPR.1990.119333