基于多尺度压缩感知的信号重构

摘要

Compressed Sensing is a new sampling theorem, it points out that if a signal can be compressed under some conditions, that a very accurate reconstruction can be obtained from a relatively small number of non-traditional samples. On the basis of compressed sensing, the paper presents multiscale compressed sensing- The numerical experiments demonstrate that multiscale compressed sensing can give better quality reconstruction than a literal deployment of the compressed sensing methodology.%压缩感知是近几年新兴的采样理论,它指出如果信号在某些基上是可压缩的,那么通过很少的观测即可获得信号的准确重构.当信号采用小波基并在压缩感知的基础上,提出了多尺度压缩感知,数值仿真结果表明多尺度压缩感知可以给出更好的重构效果.