Fuzzy image smoothing

Author

Shen, Qiang

Author_Institution

Intell. Autom. Lab., Heriot-Watt Univ., Edinburgh, UK

Volume

ii

fYear

1990

fDate

16-21 Jun 1990

Firstpage

74

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1990. Proceedings., 10th International Conference on

Conference_Location

Atlantic City, NJ

Print_ISBN

0-8186-2062-5

Type

conf

DOI

10.1109/ICPR.1990.119333

Filename

119333