基于M变换和BayesShrink方法的泊松噪声退化图像去噪

Yeqiu Li, Jianming Lu, Ling Wang, Takashi Yahagi
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引用次数: 2

摘要

中值滤波器和其他非线性滤波器已被研究用于恢复具有泊松噪声的退化图像。近年来,利用小波变换进行子带图像恢复一直备受关注。该方法对小幅度噪声有效,但在泊松噪声的情况下,大幅度噪声超过预设阈值,无法去除。在这项研究中,我们提出了一种新的方法,通过结合M变换[5]和小波贝叶斯收缩方法,从具有泊松噪声的退化图像中去除噪声。©2007 Wiley Periodicals,股份有限公司Electron Comm Jpn Pt 3,90(11):2007年11月20日;在线发表于Wiley InterScience(www.InterScience.Wiley.com)。DOI 10.1002/ecjc.20357
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Noise removal for degraded images with Poisson noise using M-transformation and BayesShrink method

Median filters and other nonlinear filters have been investigated for restoration of degraded images with Poisson noise. Recently, subband image restoration using the wavelet transform has been attracting much attention. This method is effective for small-amplitude noise, but in the case of Poisson noise, large-amplitude noise exceeds the preset threshold and is not removed. In this study, we propose a new method of noise removal from degraded images with Poisson noise by using a combination of the M-transformation [5] and the wavelet BayesShrink method. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 90(11): 11–20, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20357

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