DocumentCode :
3600237
Title :
Features preserving filters using fuzzy Kohonen clustering network in detection of impulse noise
Author :
Singh, Kh Manglem ; Bora, P.K. ; Mahanta, Anil
Author_Institution :
Dept. of Electron. & Commun. Eng., Indian Inst. of Technol., Guwahati, India
Volume :
1
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
420
Abstract :
It is always advisable to apply filtering only on corrupted pixels of images leaving untouched the uncorrupted ones to preserve image features and to avoid blurring effects. We present an algorithm which can detect the corrupted pixels in texture images. It uses a fuzzy Kohonen clustering network that integrates with the fuzzy c-means (FCM) model utilizing the updating strategies of the first and the learning rate of the second
Keywords :
feature extraction; fuzzy set theory; image texture; impulse noise; learning (artificial intelligence); median filters; pattern clustering; self-organising feature maps; corrupted pixels; feature-preserving filters; filtering; fuzzy Kohonen clustering network; fuzzy c-means model; image features; impulse noise detection; learning rate; multilevel median filter; texture images; updating; Clustering algorithms; Filtering algorithms; Filters; Fuzzy logic; Image processing; Image storage; Information filtering; Intelligent networks; Noise reduction; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2001. Proceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology
Print_ISBN :
0-7803-7101-1
Type :
conf
DOI :
10.1109/TENCON.2001.949627
Filename :
949627
Link To Document :
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