计算机工程 ›› 2012, Vol. 38 ›› Issue (9): 226-227,247.doi: 10.3969/j.issn.1000-3428.2012.09.069

• 图形图像处理 • 上一篇    下一篇

基于改进层式DCT的压缩感知图像处理

尹晓慧,张宝菊,王 为,雷 晴   

  1. (天津师范大学物理与电子信息学院,天津 300387)
  • 收稿日期:2011-10-26 出版日期:2012-05-05 发布日期:2012-05-05
  • 作者简介:尹晓慧(1987-),女,硕士研究生,主研方向:数字音/视频处理;张宝菊(通信作者),教授、博士;王 为,博士;雷 晴,硕士研究生
  • 基金项目:
    天津市自然科学基金资助项目(10JCYBJC00400);天津市高等学校科技发展基金资助项目(52J10013)

Compressed Sensing Image Processing Based on Improved Layered DCT

YIN Xiao-hui, ZHANG Bao-ju, WANG Wei, LEI Qing   

  1. (College of Physics and Electronic Information, Tianjin Normal University, Tianjin 300387, China)
  • Received:2011-10-26 Online:2012-05-05 Published:2012-05-05

摘要: 为改善图像压缩质量,提出一种基于改进层式离散余弦变换(DCT)的压缩感知图像处理方法。该方法保留层式DCT变换的最高层系数,只对其余层高频子带系数进行压缩感知随机测量。利用正交匹配追踪算法对高频系数进行恢复,通过DCT反变换重构图像。实验结果表明,与基于层式DCT的方法相比,在相同压缩比的情况下,该方法重构图像的峰值信噪比较高。

关键词: 压缩感知, 随机测量, 稀疏变换, 改进层式离散余弦变换, 图像编码

Abstract: In order to improve the quality of the compressed image, an compressed sensing method based on improved layered Discrete Cosine Transform(DCT) is proposed. It only measures the high-pass coefficients of the other layers, and preserves the top layer coefficients. For the reconstruction, high-pass coefficients can be recovered by the measurements. The image can be reconstructed by the inverse DCT transformation. Simulation results demonstrate that, at the same compression ratio, the peak signal to noise ratio of this method is higher than method based on layed DCT.

Key words: compressed sensing, random measurement, sparse transformation, improved layered Discrete Cosine Transform(DCT), image coding

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