An adaptive parameterized block-based singular value decomposition for image de-noising and compression

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• 作者：Y.-T. Shih^a ; ¹ ; ^{yintzer_shih@email.nchu.edu.tw} ; C.-S. Chien^b ; C.-Y. Chuang^a
• 关键词：Singular value decomposition ; Image compression ; Image filtering ; Image denoising
• 刊名：Applied Mathematics and Computation
• 出版年：2012
• 期刊代码：7_00963003
• 类别：cp
• 出版时间：1 July, 2012
• 卷：218
• 期：21
• 页码：10370-10385
• 文件大小：2148 K

摘要

We propose an adaptive parametrized block-based singular value decomposition (APBSVD) for preserving the edge structure and avoiding blurred image after the compressing process. We also exploit a proper selection of the Peak Signal to Noise Ratio (PSNR) parameter at each block to appropriately eliminate high-frequency noise. Our numerical results show that the proposed methods are promising which effectively remove the noise, and preserves the edge information well during the block-based SVD image compression.