CAJ | 학술논문

压缩感知理论为提升信息获取能力提供了新的思路，它表明当被探测信号具有稀疏性时，则获取信号所必需的测量数据与其稀疏度K量级相当，而远小于信号的维数N（Shannon采样定理所要求的采样数）。基于压缩感知理论的成像技术（压缩成像）则将感知、压缩和数据处理三个过程完美地结合在一起，避免了传统成像系统“先采样再压缩”方式带来的传感器和计算资源浪费。本文从稀疏性、投影测量矩阵的设计与可重构条件、压缩感知重构算法三个方面概述了压缩感知理论及进展，并以光学成像为背景，详细阐述了最近提出的几类光学压缩成像系统，最后，探讨了压缩感知及压缩成像方面目前所面临的一些挑战性问题。
압축감지이론위제승신식획취능력제공료신적사로，타표명당피탐측신호구유희소성시，칙획취신호소필수적측량수거여기희소도K량급상당，이원소우신호적유수N（Shannon채양정리소요구적채양수）。기우압축감지이론적성상기술（압축성상）칙장감지、압축화수거처리삼개과정완미지결합재일기，피면료전통성상계통“선채양재압축”방식대래적전감기화계산자원낭비。본문종희소성、투영측량구진적설계여가중구조건、압축감지중구산법삼개방면개술료압축감지이론급진전，병이광학성상위배경，상세천술료최근제출적궤류광학압축성상계통，최후，탐토료압축감지급압축성상방면목전소면림적일사도전성문제。
Compressive sensing provides a new way for increasing the ability of information acquisition.Compressive sensing asserts that it is possible to accurately reconstruct signals from sub-Nyquist sampling,provided some additional assumptions (sparse or compressible)are made about the signal in question.The compressive imaging technology,which is based on the compressive sensing theory,integrates the processes of sensing,compression and processing perfectly,avoiding the resource waste caused by a traditional “sample-then-compress”framework.With a review of some of the recent progress in compressive sensing theory from the following three aspects:sparsity,the design of measuring matrix and recovery conditions,the reconstruction algorithms,several optical compressive imaging systems are introduced,and some key challenges in this area have been discussed in the end.