基于FOCUSS的图像分块压缩感知

摘要

为了解决图像重建计算复杂度大的问题,有人提出了分块压缩感知( Block Compressed Sensing),但基于正交匹配追踪(OMP)的图像分块重建会产生明显的块效应.针对这一问题,本文提出了基于欠定系统局灶解法(FocalUnderdetermined System Solution,简称FOCUSS)的图像分块重建,算法首先对图像进行分块,然后用傅里叶变换把图像稀疏化,再用FOCUSS重建分块图像.仿真实验结果表明,基于FOCUSS的图像分块重建不仅降低了图像块效应,而且提高了重建图像质量.%In order to solve the problem of the computational complexity of image reconstruction, block compressed sensing method has been proposed. However, this method might generate a weakness that the image reconstructed by using orthogonal matching pursuit ( OMP) has obvious block effect. In order to weaken the block effect, this paper has proposed an image reconstruction algorithm based on Focal Underdetermined System Solution ( abbreviation FOCUSS). Firstly, the image should be divided into a few blocks. Then we can use Fourier transform to make the image sparse. Finally, original image can be reconstructed by using FOCCUS. The simulation results illustrate that the image block reconstruction based on FOCUSS has greatly reduced the block effect and improved the quality of reconstructed image.