DocumentCode :
3603998
Title :
Image denoising using common vector approach
Author :
O?Œ?†zkan, Kemal ; Seke, Erol
Author_Institution :
Comput. Eng. Dept., Eskisehir Osmangazi Univ., Meselik, Turkey
Volume :
9
Issue :
8
fYear :
2015
Firstpage :
709
Lastpage :
715
Abstract :
Common vector approach (CVA) is an increasingly popular classification method in recognition problems where probability of having the dimensionality of the problem higher than the number of data items is not zero. In CVA, common component of the members of classes is separated from the discriminating difference parts and used to determine whether a given vector (a block of data) belongs to the class in question, or to find out the class it belongs to. In this study, overlapping image blocks near the current pixel to be denoised are used as input data and a class is constructed per pixel position. Denoised image block is then constructed with the sum of common vector of the class and difference vector of the centre block denoised by linear minimum mean square error estimation technique. Since the classes are formed using similar blocks, the edges are preserved while denoising the image.
Keywords :
estimation theory; image classification; image denoising; mean square error methods; probability; vectors; CVA; common vector approach; image classification method; image denoising; image recognition; linear minimum mean square error estimation technique; probability;
fLanguage :
English
Journal_Title :
Image Processing, IET
Publisher :
iet
ISSN :
1751-9659
Type :
jour
DOI :
10.1049/iet-ipr.2014.0979
Filename :
7166434
Link To Document :
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