空间频率与方向特征相结合的自适应采样压缩感知算法

An Adaptive Sampling Method of Compressed Sensing by Combining Spacial Frequency with Direction Features

在分块压缩感知采样过程中,为根据图像块特征更合理的分配采样率,提出一种基于纹理特征的图像分块自适应采样压缩感知算法.首先使用空间频率提取图像块纹理信息;其次根据纹理信息将图像块分为平滑块或纹理块,并确定各块的基础采样率;再使用基础采样率对平滑块采样,在基础采样率的基础上结合小波域系数统计特征调整纹理块子带系数采样率;最后使用平滑投影Landweber重建图像.实验结果证明,与已有的图像分块压缩感知算法相比,当压缩率适中时,无论是视觉效果还是客观指标方面,该算法均能明显地提高图像信号重建质量.

In the procedure of sampling of block compress sensing, to fully make use of features of image blocks for more reasonable sampling rate, this paper proposes an adaptive sampling algorithm of block- divided compressed sensing for images based on textural feature. First, the spacial frequency is utilized to extract the textural features of image blocks; Second, each block is categorized into the smooth blocks or the textual blocks based on the textual features, and the basic sampling rate is obtained simultaneously; Third, we adjust the subrate of subbands using the statistical characteristics of the coefficients in wavelet domain based on basic sample rate for the textural blocks. Finally, the smooth projected Landweber is employed to reconstruct images. The experiment results show that when the compressing ratio is modest, the quality of reconstructed images can be improved greatly by the proposed algorithm comparing with other block-based compressed sensing algorithms from the aspects of objective indicator and visual effect.