Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/2919
Title: Improved Wavelet Shrinkage Technique for Image Denoising
Authors: KHELALEF Aziz , HIMEUR Yassine,GUERMOUI Mouloud
Keywords: wavelet thresholding
Cycle Spinning
Wavelet Transform
shrinkage
image denoising
Issue Date: 19-Dec-2013
Abstract: In this paper, we propose a new wavelet-based image denoising algorithm that is based on a state-of-the-art algorithm, namely FAS (Feature Adaptive shrinkage). Two modifications are introduced in order to increase its efficiency. This consists of developing a new shrinkage function which is adapted to each level of decomposition. Also, we combined the new scheme with the cycle spinning algorithm in order to resolve the pseudo Gibbs phenomena problem. A number of experiments, carried out on various test images, demonstrate significant improvement over the conventional FAS and against other wavelet denoising methods.
Description: The INTERNATIONAL CONFERENCE ON ELECTRONICS & OIL: FROM THEORY TO APPLICATIONS March 05-06, 2013, Ouargla, Algeria
URI: http://hdl.handle.net/123456789/2919
ISSN: waf
Appears in Collections:2. Faculté des nouvelles technologies de l’information et de la communication

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