自动化学报Issue(1)：22-37,16.DOI:10.16383/j.aas.2015.c140087
动态压缩感知综述
A Survey on Dynamic Compressed Sensing
摘要
Abstract
In video signal processing, dynamic compressed sensing (DCS) is a novel branch of compressed sensing (CS) theory for recovery of compressible, possibly with a slowly varying sparsity pattern, signal from a time sequence of noisy observations. Dynamic compressed sensing has been employed in dynamic magnetic resonance image reconstruction successfully. The system model for dynamic compressed sensing is first introduced, including definitions of slowly varying supports, sparse representations and stable measurement of the time-varying sparse signal. Then, a unified framework is formulated for reconstruction of the time-varying sparse signal. Based on the framework, classification is conducted for the existing algorithms whose main ideas, reconstruction procedures and performance are also commented briefly. Finally, the applications and future directions of dynamic compressed sensing are pointed out.关键词
动态压缩感知/时变稀疏信号/动态测量/卡尔曼滤波/视频压缩感知Key words
Dynamic compressed sensing (DCS)/time-varying sparse signals/dynamic measurement update/Kalman filter/video compressed sensing引用本文复制引用
荆楠,毕卫红,胡正平,王林..动态压缩感知综述[J].自动化学报,2015,(1):22-37,16.基金项目
国家自然科学基金(61303233,61201263,61102110),河北省高等学校科学技术研究青年基金(QN20131058),河北省自然科学基金(F2014203062)资助Supported by National Natural Science Foundation of China (61303233,61201263,61102110), Natural Science Research Pro-grams of Hebei Educational Committee for University Young Teachers (QN20131058), and National Natural Science Founda-tion of Hebei (F2014203062) （61303233,61201263,61102110）
