J4 ›› 2010, Vol. 28 ›› Issue (05): 439-.

• 论文 • 上一篇    下一篇

几种图像变换算法性能比较

田润澜|肖卫华|齐兴龙   

  1. 空军航空大学 航空电子工程系|长春 130022
  • 出版日期:2010-09-30 发布日期:2010-10-28
  • 通讯作者: 田润澜(1973— ),女,河北唐山人,空军航空大学讲师,主要从事通信、图像压缩、视频压缩研究,(Tel)86-13604409370(E-mail) E-mail:runlantt@sohu.com。
  • 作者简介:田润澜(1973— )|女|河北唐山人|空军航空大学讲师|主要从事通信、图像压缩、视频压缩研究|(Tel)86-13604409370(E-mail) runlantt@sohu.com。

 Comparion of Servral Image Transform

TIAN Run-lan|XIAO Wei-hua|QI Xing-long   

  1. Department of Aviation Electronical Engineering,Aviation University of Air Force, Changchun 130022|China
  • Online:2010-09-30 Published:2010-10-28

摘要:

为寻找提高图像压缩算法性能的途径,比较了二维DCT(Discrete Cosine Transform)变换,二维张量积小波变换以及最新的几何小波的变换特点及实用效果。针对同一图像采用不同的几何小波进行分解,保留相同个数的显著系数进行图像重建,以比较各种小波基的稀疏表示能力。结果显示,在高压缩比条件下,Bandelet和DCT变换更加有效,而在高质量条件下,小波变换依旧是最有效的工具。

关键词: 图像压缩, 小波, 楔波, 曲波, 边缘波, Bandelet

Abstract:

 In order to find a way to improve the performance of image compression, the characteristic and effect of 2D-DCT(Discrete Cosine Transform), twodimensional tensor product wavelet,and the latest geometrical wavelet are compared. The same image is decomposed with different geometrical wavelet and then reconstructed with the same number of significant coefficients, thus the sparse representation capability of wavelet can be compared, the result shows that Bandelet and DCT are more efficient when require high compression ratio, while wavelet is still the most efficient tool when require high image quality.

Key words: image compression, wavelet, wedgelets, curvelets, contourlets, bandelet

中图分类号: 

  • TN911.7