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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Image denoising with neighbour dependency and customized wavelet and threshold
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Image denoising with neighbour dependency and customized wavelet and threshold

机译:具有邻居依赖性和自定义小波和阈值的图像去噪

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摘要

Image denoising by means of wavelet transforms has been an active research topic for many years. For a given noisy image, which kind of wavelet and what threshold we use should have significant impact on the quality of the denoised image. In this paper, we use Simulated Annealing to find the customized wavelet filters and the customized threshold corresponding to the given noisy image at the same time. Also, we propose to consider a small neighbourhood around the customized wavelet coefficient to be thresholded for image denoising. Experimental results show that out, approach is better than VisuShrink, our NeighShrink with fixed wavelet, and the wiener2 filter that is available in Matlab Image Processing Toolbox. In addition, our NeighShrink with fixed wavelet already outperforms VisuShrink for all the experiments. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
机译:多年来,利用小波变换进行图像去噪一直是一个活跃的研究课题。对于给定的噪点图像,我们使用哪种小波以及使用哪种阈值应该对去噪图像的质量产生重大影响。在本文中,我们使用“模拟退火”来找到定制的小波滤波器和与给定噪声图像对应的定制阈值。此外,我们建议考虑在定制小波系数周围的小邻域阈值以进行图像降噪。实验结果表明,该方法优于VisuShrink,具有固定小波的NeighShrink和Matlab图像处理工具箱中提供的wiener2滤波器。此外,在所有实验中,带有固定小波的NeighShrink都比VisuShrink更好。 (C)2004模式识别学会。由Elsevier Ltd.出版。保留所有权利。

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