基于两步迭代收缩法的多稀疏空间图像快速重构方法

A Fast Reconstruction Method of Multi-Sparse Space Image Based on Two-Step Iterative Shrinkage Method

由于多稀疏空间图像重构时,像素范围选取过大、峰值信噪比低以及重构时间长,导致图像重构方法存在重构效果差的问题,提出基于两步迭代收缩法的多稀疏空间图像快速重构方法。明确多稀疏空间图像重构存在的问题,在明确问题后,以迭代收缩阈值算法为基础,引入迭代加权收缩算法,结合每一轮迭代结果作为初值,完成图像重构的两步迭代收缩法设计,实现多稀疏空间图像快速重构。实验结果表明:应用该方法后的重构多稀疏空间图像峰值信噪比达到37.9 dB以上,图像重构时间仅为16.0 ms,图像结构相似性达到了0.98以上,并且重构多稀疏空间图像的效果更好,经过实验分析证实了所提方法具备可行性。

Image reconstruction methods have the problem of poor reconstruction effect due to the large pixel range selection,low peak signal-to-noise ratio and long reconstruction time in multi-sparse space image reconstruction.A fast reconstruction method of multi-sparse space image based on two-step iterative contraction is proposed.The problems existing in multi-sparse space image reconstruction were clarified.The iterative weighted shrinkage algorithm was introduced based on the iterative shrinkage threshold algorithm after iden-tifying the problems,and the results of each iteration were combined as initial values,the two-step iterative shrinkage method design of image reconstruction was completed to realize the rapid reconstruction of multi-sparse space image.The experimental results show that the peak signal-to-noise ratio of reconstructed multi-sparse space images can reach more than 37.9 dB,image reconstruction time is only 16.0 ms,the image structure similarity can reach more than 0.98,and the reconstruction effect of multi-sparse space images is better.