基于四叉树分割的分形图像压缩及新的快速分类策略

U. Nandi, J. K. Mandal, S. Santra, Suman Nandi
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引用次数: 11

摘要

本文提出了一种基于四叉树分割技术的分形图像压缩快速分类策略。该方案显著减少了图像编码过程中的均方误差(MSE)计算次数。从压缩比、压缩时间和PSNR三个方面比较了现有和提出的分类策略对分形图像的压缩性能。这两种技术都使用四叉树分区方案。所提出的分类策略显著缩短了分形图像压缩技术的压缩时间,使其压缩比和PSNR保持基本一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fractal image compression with quadtree partitioning and a new fast classification strategy
In this paper, a new fast classification strategy is proposed for fractal image compression with quadtree partitioning technique. The scheme significantly reduces the number of mean square error (MSE) computations during encoding of images. Performance in terms of compression ratios, compression time and PSNR of the fractal image compression with existing and proposed classification strategy are compared. Both techniques use quadtree partitioning scheme. The proposed classification strategy reduces the compression time significantly of the fractal image compression technique maintaining compression ratio and PSNR almost same with its counterpart.
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