Title :
Multi-level adaptive fuzzy filter for mixed noise removal
Author :
Peng, Shaomin ; Lucke, Lori
Author_Institution :
Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA
fDate :
30 Apr-3 May 1995
Abstract :
Combination or hybrid filters utilize linear and nonlinear techniques to remove noise from an image while preserving details. Typically these filters are trained to remove either Gaussian or impulsive noise. They cannot remove large amounts of mixed noise. In this paper we present a new multi-level adaptive fuzzy (MLAF) filter for mixed noise removal during image processing. This filter utilizes fuzzy sets to combine linear and nonlinear techniques and effectively removes large amounts of mixed Gaussian and impulsive noise while preserving the image details. Experimental results are included to demonstrate the effectiveness of the proposed filter
Keywords :
Gaussian noise; adaptive filters; filtering theory; fuzzy set theory; image enhancement; interference suppression; nonlinear filters; Gaussian noise; fuzzy sets; image processing; impulsive noise; linear techniques; mixed noise removal; multilevel adaptive fuzzy filter; nonlinear techniques; Adaptive filters; Additive noise; Computed tomography; Fuzzy sets; Gaussian noise; Image processing; Information filtering; Noise level; Nonlinear filters; Pixel;
Conference_Titel :
Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2570-2
DOI :
10.1109/ISCAS.1995.521425