Compressive Coded Apertures for High-Resolution Imaging

被引:9
|
作者
Marcia, Roummel F. [1 ]
Harmany, Zachary T. [2 ]
Willett, Rebecca M. [2 ]
机构
[1] Univ Calif, Sch Nat Sci, Merced, CA 95344 USA
[2] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA
关键词
Compressive sensing; coded aperture; sparse recovery; model-based sparsity; wavelets; SIGNAL RECONSTRUCTION;
D O I
10.1117/12.849487
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Traditionally, optical sensors have been designed to collect the most directly interpretable and intuitive measurements possible. However, recent advances in the fields of image reconstruction, inverse problems, and compressed sensing indicate that substantial performance gains may be possible in many contexts via computational methods. In particular, by designing optical sensors to deliberately collect "incoherent" measurements of a scene, we can use sophisticated computational methods to infer more information about critical scene structure and content. In this paper, we explore the potential of physically realizable systems for acquiring such measurements. Specifically, we describe how given a fixed size focal plane array, compressive measurements using coded apertures combined with sophisticated optimization algorithms can significantly increase image quality and resolution.
引用
收藏
页数:11
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