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Removal of Gaussian noise from degraded images in wavelet domain
Author(s) -
Li Yeqiu,
Lu Jianming,
Wang Ling,
Yahagi Takakshi
Publication year - 2008
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.10029
Subject(s) - gaussian noise , wavelet , noise (video) , median filter , salt and pepper noise , wiener filter , gaussian , noise measurement , computer science , noise reduction , gradient noise , amplitude , algorithm , gaussian filter , wavelet transform , value noise , mathematics , gaussian blur , image (mathematics) , artificial intelligence , noise floor , image restoration , physics , image processing , optics , quantum mechanics
Observed images are often corrupted by Gaussian noise. If the image is embedded in small‐amplitude Gaussian noise, the noise can be removed by applying a Wiener filter. Recently, the BayesShrink wavelet method has attracted considerable attention as a denoising technique. In this paper, we propose a method for removal of Gaussian noise of large amplitude as well as of small amplitude which cannot be removed only by exploiting the BayesShrink wavelet method. Our approach is a combination of the BayesShrink wavelet method with the directional adaptive center‐weighted median filter. Applying the proposed method to an image corrupted by large‐amplitude Gaussian noise, a clean image can be obtained. © 2008 Wiley Periodicals, Inc. Electron Comm Jpn, 91(1): 11–18, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10029
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