基于压缩感知的可见光域叠层衍射成像理论与实验研究

项目名称： 基于压缩感知的可见光域叠层衍射成像理论与实验研究

项目编号： No.61307018

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 王雅丽

作者单位： 中国科学院大学

项目金额： 26万元

中文摘要： 针对目前成像领域分辨率与高数据量之间的矛盾，提出了将压缩感知理论应用于叠层衍射成像，以达到降低获取数据量获得高分辨率复振幅成像的目的。本项目首先研究并设计压缩采样原理应用于叠层衍射成像中的稀疏矩阵构建及求解算法；光学成像系统中测量矩阵的构建方法及复振幅图像的重算法。提出了采用照明探针随机稀疏入射以及随机相位调制稀疏信号两种模式实现压缩采样。设计两种对应模式的稀疏矩阵和优化测量矩阵，构建简单的、强健的、对采样矩阵限制较少的基于此理论的相位恢复算法。建立实验系统，进行可见光域实验，验证算法的有效性。此外，探索基于压缩感知的叠层成像进行超分辨成像的研究。本项目的研究为压缩感知应用于其他波段提供一个研究基础，并且揭示了压缩感知理论在高分辨率成像、实时成像等诸多领域潜在的应用价值。

中文关键词： 叠层成像；衍射成像；超分辨；；

英文摘要： The high resolution imaging of complex amplitude will be obtained due to the application in ptychography diffractive imaging based on a theory of compressed sensing. That can solve the contradiction between large amounts of data and resolution. The project will research on algorithm of sparse matrix of compressive sensing applied in ptychography diffractive imaging, and the algorithm of measurement matrix in optical system and the algorithm of the image reconstruction of complex amplitude. Two models of achieving the compressive sampling are proposed that are the random illumination probe and the random phase modulation for sparse signal. The sparse matrix and the optimizational measurement matrix will be designed. The phase retrieval algorithm will be constructed that is simple and robust and less limitation for sampling matrix. The experimental system will be established in visible light domain. The effectiveness of the algorithm will be validated. In addition, the super resolution imaging will be explored in the ptychographical imaging based on compressed sensing. The project provide a research basis for the application of compressed sensing in other bands and reveals the potential application value of the compressed sensing theory in the high resolution imaging, real-time imaging, and many other areas.

英文关键词： Ptychography imaging；diffractive imaging；super-resolution；；