Title :
A fuzzy operator for the enhancement of blurred and noisy images
Author :
Russo, Fabrizio ; Ramponi, Giovanni
Author_Institution :
Dipartimento di Elettrotecnica Elettronica ed Inf., Trieste Univ., Italy
fDate :
8/1/1995 12:00:00 AM
Abstract :
Rule-based fuzzy operators are a novel class of operators specifically designed in order to apply the principles of approximate reasoning to digital image processing. This paper shows how a fuzzy operator that is able to perform detail sharpening but is insensitive to noise can be designed. The results obtainable by the proposed technique in the enhancement of a real image are presented
Keywords :
fuzzy set theory; image enhancement; inference mechanisms; knowledge based systems; noise; approximate reasoning; blurred images; detail sharpening; digital image processing; image enhancement; noisy images; rule-based fuzzy operators; Digital images; Fuzzy reasoning; Fuzzy set theory; Fuzzy sets; Humans; Image enhancement; Image processing; Pattern recognition; Pixel; Smoothing methods;
Journal_Title :
Image Processing, IEEE Transactions on
