边缘和方向估计的自适应多尺度分块压缩感知算法

由于多尺度小波变换的分块压缩感知算法(MS-BCS-SPL）将每层子带信息进行分块时，使得每子带中各子块采用相同的采样率；但是，当不同的图像子块含有不同的边缘信息时，对这些子块采用相同的采样率会造成资源不合理的分配。因此在MS-BCS-SPL算法的基础上，利用图像块边缘信息的不同和图像块的方向性，将总的采样率自适应分配给各层子带中的各图像块，实现多尺度分块压缩感知的自适应采样。实验结果表明，在不同采样率，尤其较低采样率时，该算法不仅比MS-BCS-SPL算法采用了较少的采样数目，节约资源；而且比其可重构较高质量的图像。 

Adaptive Multi-scale Block Compressed Sensing Algorithm Based on Edge And Direction Estimation

Because the multi-scale block compressed sensing algorithm(MS-BCS-SPL) made each sub-band information to block which had the same sampling rate, while this would cause the unreasonable distribution of resources when these blockes had different edge information. Therefore on the basis of MS-BCS-SPL algorithm, we assigned adaptively the total sampling rate to each block of each layer of sub-band using the different edge information and directional of image blockes, to realize adaptive multi-scale block compressed sensing. Experiments show that, with the different sampling rate especially lower sampling rate, this algorithm not only use less samples and conserve resources; but also recovery more high quality images than the original algorithm.