一种基于全变差莫型的欠采样图像重构方法

摘要

A new image reconstruction algorithm was proposed based on the TV norm minimization model. Then using the under sampling fusion information, combined with the image reconstruction algorithm, a fusion model based on compressed sensing is proposed. Numerical results show that the proposed image reconstruction method can reduce the sampling number required to some extent compared with the traditional algorithm. The proposed fusion model has good performance for many kinds of images.%基于全变差范数最小化模型,构造了一种新的图像重构算法；利用欠采样域内的融合信息,结合构造的图像重构算法,提出了一种基于压缩感知理论的图像融合模型.数值实验表明,构造的重构算法与传统算法相比,在一定程度上减少了所需的采样数量；提出的融合模型对多类图像具有较优的融合效果.