Image Reconstruction Based on Compressed Sensing with Split Bregman Algorithm and Fuzzy Bases
When original data is not complete or image degenerates, image reconstruction and recovery will be very important. In order to acquire reconstruction or recovery image with good quality, compressed sensing provides the possibility of achieving, and an image reconstruction algorithm based on compressed sensing with split Bregman method and fuzzy bases sparse representation is proposed, split strategy is applied in split Bregman algorithm in order to accelerate convergence speed; At the same time, discrete cosine transform and dual orthogonal wavelet transform are treated as bases to represent image sparsely, and image is reconstructed by using split Bregman algorithm. Experiments show that the proposed algorithm can improve convergence speed and reconstruction image quality.
Compressed Sensing Image Reconstruction Split Bregman Algorithm Fuzzy Bases.
Cui Jianjiang Jia Xu Liu Jing Li Qi
No.11, Lane 3, Wenhua Road, Heping District, Shenyang, China
国际会议
上海
英文
80-83
2011-10-27（万方平台首次上网日期，不代表论文的发表时间）