自动化学报Issue(8)：1563-1575,13.DOI:10.3724/SP.J.1004.2014.01563
压缩感知及其图像处理应用研究进展与展望
Advances and Perspective on Compressed Sensing and Application on Image Processing
摘要
Abstract
Compressed sensing (CS) can perceive the original structure of signals through a few measured values, and reconstruct the signal by solving an optimal problem accurately. The theory of CS not only reduces the cost of the storage and transmission during the acquisition of images and videos, but also provides new opportunities for the follow-up image processing and recognition, promoting the combination of theory and engineering application. This paper presents the principles of CS, and surveys the latest theory achievements and development of sparse representation, design of measurement matrix and reconstruction algorithm. Then this paper analyzes and discusses the research and development of CS theory in its application of image processing field. In the end, the paper points out the existing problems and the future application.关键词
压缩感知/稀疏表示/观测矩阵/重构算法/图像处理Key words
Compressed sensing/sparse representation/measurement matrix/reconstruction algorithm/image processing引用本文复制引用
任越美,张艳宁,李映..压缩感知及其图像处理应用研究进展与展望[J].自动化学报,2014,(8):1563-1575,13.基金项目
国家自然科学基金(61231016,61301192,61272288,61201291),河南省科技攻关计划(142102210557),西北工业大学基础研究基金(JCT20130108, JC201120, JC201148)资助Supported by National Natural Science Foundation of China (61231016,61301192,61272288,61201291), Key Science and Technology Program of Henan Province (142102210557), NPU Foundation for Fundamental Research (JCT20130108, JC201120, JC201148) （61231016,61301192,61272288,61201291）
