thepage的变换误差矢量旋转码本中基于Kekre、Walsh和倾斜小波变换的矢量量化图像压缩

Sudeep D. Thepade, J. Dewan, Bhavana V. Suryawanshi, S. Erandole
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引用次数: 2

摘要

图像形式的数据库已大大增加。缺乏可用的存储空间和带宽是图像数据库管理面临的主要限制。大多数应用程序需要快速传输图像文件和高效存储。图像压缩为所有这些情况提供了可能的解决方案。它在不降低图像质量到一定程度的情况下,将图像表示为压缩格式,使其看起来与原始图像相同。矢量量化(VQ)是一种有损但有用的图像压缩技术。本文采用thepage的变换误差矢量旋转(TTEVR)算法,采用Kekre、Walsh、Slant正交变换和Kekre、Walsh、Slant变换各自的小波变换进行码本生成。实验在13张尺寸分别为256×256×3和512×512×3的混合图像的测试台上进行,码本尺寸分别为256和512。结果表明,用Kekre小波变换生成的码本大小为256和512,与本文考虑的所有其他变换相比,压缩质量更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vector quantization based image compression with Kekre, Walsh and Slant Wavelet transforms in Thepade's Transform Error Vector Rotation codebooks
The database in the form of images has increased up to huge extent. Lack of storage space and bandwidth available are the main limitations faced to manage image databases. Most of the applications required fast transmission of image files and efficient storage. Image compression gives possible solution for all these conditions. It represents an image into reduced format without degrading its quality up to certain level so that it seems same as original image. Vector quantization (VQ) is lossy but useful technique of image compression. In this paper, Thepade's Transform Error Vector Rotation (TTEVR) algorithm with Kekre, Walsh, Slant orthogonal transforms and respective Wavelet Transform of Kekre, Walsh and Slant transforms are used for codebook generation. The experimentation is conducted with codebook sizes of 256 and 512 on a testbed of 13 assorted images of size 256×256×3 and 512×512×3. Results show that the codebook of size 256 and 512 generated from TTEVR with Kekre Wavelet Transform gives better compression quality as compared to all other transforms considered here.
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