Adaptive compressive imaging for object reconstruction

Jun Ke*, Amit Ashok, Mark A. Neifeld

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Static Feature-specific imaging (SFSI) employing a fixed/static measurement basis has been shown to achieve superior reconstruction performance to conventional imaging under certain conditions.1-5 In this paper, we describe an adaptive FSI system in which past measurements inform the choice of measurement basis for future measurements so as to maximize the reconstruction fidelity while employing the fewest measurements. An algorithm to implement an adaptive FSI system for principle component (PC) measurement basis is described. The resulting system is referred to as a PC-based adaptive FSI (AFSI) system. A simulation study employing the root mean squared error (RMSE) metric to quantify the reconstruction fidelity is used to analyze the performance of the PC-based AFSI system. We observe that the AFSI system achieves as much as 30% lower RMSE compared to a SFSI system.

源语言英语
主期刊名Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems II
DOI
出版状态已出版 - 2010
已对外发布
活动Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems II - San Diego, CA, 美国
期限: 1 8月 20102 8月 2010

出版系列

姓名Proceedings of SPIE - The International Society for Optical Engineering
7818
ISSN(印刷版)0277-786X

会议

会议Adaptive Coded Aperture Imaging, Non-Imaging, and Unconventional Imaging Sensor Systems II
国家/地区美国
San Diego, CA
时期1/08/102/08/10

指纹

探究 'Adaptive compressive imaging for object reconstruction' 的科研主题。它们共同构成独一无二的指纹。

引用此