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標題: 以參數化區塊奇異值分解做壓縮和去除雜訊
Parameterized Block-Based Singular Value Decomposition for Image Compression and Denoising
作者: 莊佳芸
Chuang, Chia-Yun
關鍵字: Singular value decomposition
image compression
image denoising
出版社: 應用數學系所
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摘要: 一些傳統性的濾波器會使得影像的細節資訊模糊化,在這個論文我們提出兩個以區塊SVD 為基礎的方法。它同時可以用於影像壓縮以及雜訊去除。此方法主要是使用限制每個區塊的PSNR 值將高頻資訊予以適當的去除,並以SVD 型態儲存,以便將來影像重建。為了要得到更好的影像重建效果,我們再提出將傳統的平滑式濾波器與我們所提出的以SVD 為基礎之濾波器作結合。經由實驗結果發現,平滑式濾波器和SVD 濾波器混合使用會比原先個別濾波器有更好的結果,不但能保有影像細節並且有效去除高斯雜訊。
Some traditional filtering techniques blur the image. In order to have a good image quality for preserving the edge structure, we propose two variants of block-based singular value decomposition (BSVD) filters. We exploit that a proper selection of the PSNR parameter on each block can appropriately eliminate the high-frequency information. It is not only used for image compression, but also denoising. Numerical experiments show the great promise in our proposed methods that effectively remove the noise and preserve the edge information.
其他識別: U0005-0307200819233500
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