摘要
相位成像的关键是相位恢复。由于相位信息的丢失,相位恢复通常是不适定的,如何利用合适的先验信息进行相位恢复是一个重要问题。该文在SPICA成像系统下提出了基于结构稀疏性的单次曝光相位成像算法。该算法利用图像全变差的重叠组结构稀疏性,将重叠的结构稀疏正则项以卷积形式表示,使求解过程更简单,并利用最速下降法求解相应的优化问题。实验结果表明,该算法在有噪声的情况下能够有效地实现对复图像的重构。
The key issue in phase imaging is phase retrieval. Due to the loss of the phase information, the phase retrieval problem is usually ill-posed. How to realize the phase retrieval by using appropriate prior information is an important problem. In this work, based on single-shot phase imaging with a coded aperture, a single-shot phase imaging algorithm, which uses the structural sparsity, is proposed. The proposed algorithm exploits the overlapping structural sparsity of the total variation, and represents the structural sparsity in the form of convolution, making the problem easy to solve. Moreover, the steepest descent method is utilized to solve the corresponding optimization problem. The experiment results show that the complex amplitude can be reconstructed from noisy diffraction pattern using the proposed algorithm.
出处
《电子与信息学报》
EI
CSCD
北大核心
2017年第7期1546-1553,共8页
Journal of Electronics & Information Technology
基金
国家自然科学基金(61471313)
河北省自然科学基金(F2014203076)~~
关键词
相位恢复
结构稀疏
全变差
最速下降法
Phase retrieval
Structural sparsity
Total variation
The steepest descent method
