Title :
Speckle noise reduction using an interval type-2 fuzzy sets filter
Author :
Bigand, Andre ; Colot, Olivier
Author_Institution :
LISIC, ULCO, Calais, France
Abstract :
Fuzzy sets which capture the meaning representation of linguistic variables have been widely used in image processing in the last decades. Fuzzy sets are associated with vagueness which is type 1 uncertainty. Interval-valued fuzzy sets (IVFS) are associated with type 2 semantic uncertainty. Indeed, the length of the interval provides the "`non-specifity" measure for IVFS. We investigate this particular information measure applied to low-level image processing. This method can be used for both smoothing and noise filtering and applications in speckle noise reduction show the interest of this concept.
Keywords :
computer vision; filtering theory; fuzzy set theory; image denoising; smoothing methods; IVFS; computer vision; information measure; interval type-2 fuzzy set filter; interval-valued fuzzy sets; linguistic variables; low-level image processing; noise filtering; nonspecifity measure; smoothing method; speckle noise reduction; type-1 uncertainty; type-2 semantic uncertainty; Entropy; Fuzzy sets; Image restoration; Noise; Speckle; Uncertainty; Interval type-2 fuzzy sets; computer vision; low-level image processing; speckle filtering;
Conference_Titel :
Intelligent Systems (IS), 2012 6th IEEE International Conference
Conference_Location :
Sofia
Print_ISBN :
978-1-4673-2276-8
DOI :
10.1109/IS.2012.6335115
