Abstract: Aiming at the contradiction between the quality of image reconstruction and the quantity of coefficient sampling, the Compress Sensing(CS) algorithm based on the wavelet transform is proposed in this paper. It discusses the sparsity of image coefficient after multi-scale transform. The high-pass wavelet coefficients of the image are measured and the low-pass wavelet coefficients are preserved. The Orthogonal Matching Pursuit(OMP) algorithm is used for reconstruction of compress sensing. Simulation result demonstrates that the proposed algorithm can improve the quality of the recovered image significantly.

Key words: Compressed Sensing(CS), wavelet transform, multi-scale, orthogonality, sampling

摘要： 针对图像变换后系数采样数量和图像重建质量之间的矛盾，从图像的结构和纹理特性出发，提出基于小波变换的图像压缩感知算法。讨论图像经过多尺度小波变换后系数的稀疏性，保留图像变换后的低频系数，只对高频系数进行测量，同时利用正交匹配追踪算法重构高频系数。实验仿真结果表明，该算法能有效提高图像重建质量。

关键词: 压缩感知, 小波变换, 多尺度, 正交, 采样

CLC Number: 

• TP391