奇异值分解的一种新变体

Heri Prasetyo, D. Rosiyadi, Iwan Setiawan
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引用次数: 2

摘要

提出了一种新的图像压缩奇异值分解(SVD)计算方法。它通过两个额外的预处理步骤来修改SVD操作,即像素交错和线性化过程。首先对输入图像进行像素交错置乱处理。在应用奇异值分解计算之前,将交错图像进一步线性化。如实验结果部分所述,与经典的基于奇异值分解的技术相比,这种简单的方法在图像压缩任务中产生了有希望的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Variation of Singular Value Decomposition
This paper presents a new variation of Singular Value Decomposition (SVD) computation for image compression. It modifies the SVD operation with two additional pre-processing steps, i.e. Pixel Interleaving and Linearization process. An input image is firstly scrambled by Pixel Interleaving operation. This interleaved image is further linearized before applying SVD calculation. As documented in the Experimental Results Section, this simple approach yields a promising result in the image compression task compared to that of the classical SVD-based technique.
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