DocumentCode
693848
Title
Sonar Image Denoising via Adaptive Overcomplete Dictionary Based on K-SVD Algorithm
Author
Di Wu ; Yuxin Zhao ; Lijuan Chen ; Kuimin Wang
Author_Institution
Coll. of Autom., Harbin Eng. Univ., Harbin, China
fYear
2013
fDate
14-16 Nov. 2013
Firstpage
6
Lastpage
9
Abstract
In order to remove the noise of sonar image more effectively, the adaptive over complete dictionary based on K-SVD algorithm is carried out in this paper. Given a set of training signals from noisy image, the predefined dictionary is trained so that the new dictionary leads to the best sparse representation for sonar image, but not for the noise. Experiments are provided to demonstrate the performance of the proposed method, as compared with other denoising methods. Results show that this method, which has the capability of adaptation, is particularly appealing in terms of both denoising effect and keeping details, and has improved performance over traditional methods.
Keywords
image denoising; singular value decomposition; sonar imaging; K-SVD algorithm; adaptive overcomplete dictionary; sonar image denoising; sparse representation; training signals; Dictionaries; Filtering algorithms; Image denoising; Noise; Noise measurement; Noise reduction; Sonar; K-SVD; image denoising; overcomplete dictionary; sonar image;
fLanguage
English
Publisher
ieee
Conference_Titel
Business Intelligence and Financial Engineering (BIFE), 2013 Sixth International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4799-4778-2
Type
conf
DOI
10.1109/BIFE.2013.2
Filename
6961079
Link To Document