DocumentCode :
2058646
Title :
Extended Basis Pursuit Model and Its Application in Image De-noising
Author :
Liang, Dian-Nong ; Zhu Ju-Bo ; Wang Chun-Ling ; Liang Dian-Nong
Author_Institution :
Dept. of Math., Nat. Univ. of Defence Technol., Changsha, China
fYear :
2009
fDate :
11-14 Aug. 2009
Firstpage :
295
Lastpage :
299
Abstract :
Traditional Basis Pursuit model is adapted to signal de-noising under additive Gaussian noise. Based on the different fitness error term, one new kind Extended Basis Pursuit De-Noising (EBPDN) model is brought forward and applied into salt-and-pepper noise removal. A comparison study of performance of the median filter, the peak-and-valley filter, the detail preserving filter and the EBPDN model is carried out using different types of images. EBPDN model can provide good de-noising results and outperforms other filters in terms of noise suppression and detail preservation.
Keywords :
Gaussian noise; image denoising; median filters; additive Gaussian noise; extended basis pursuit denoising model; fitness error term; image denoising; median filter; noise suppression; peak-and-valley filter; salt and pepper noise removal; signal denoising; Additive noise; Dictionaries; Filters; Gaussian noise; Image denoising; Mathematical model; Noise reduction; Pixel; Signal denoising; Working environment noise; Basis Pursuit; Image De-noising; sparse representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Graphics, Imaging and Visualization, 2009. CGIV '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3789-4
Type :
conf
DOI :
10.1109/CGIV.2009.85
Filename :
5298848
Link To Document :
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