Compressive and adaptive imaging for target exploitation

Robert Muise; Abhijit Mahalanobis

doi:10.1117/12.832025

24 August 2009 Compressive and adaptive imaging for target exploitation

Robert Muise, Abhijit Mahalanobis

Proceedings Volume 7442, Optics and Photonics for Information Processing III; 74420A (2009) https://doi.org/10.1117/12.832025
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

Compressive sensing of imagery is a topic of much current research activity. The general field was started by Candès, Romberg, and Tao [1] when considering signals which are Sparse in the Fourier domain. This was generalized to signals sparse in general bases by Candes and Tao [2]. Donoho [3] considered further lines of research in his paper in 2006. The field is growing rapidly with new models for sparsity and algorithms for signal reconstruction being presented in the literature regularly. For signal processing applications, the speed of research and development towards particular applications has been remarkable. The application termed "analog-to-Information" has been researched extensively and an architecture for sampling wide-band signals is given by Laska, et. al. [4]. The possible applications involving image acquisition and exploitation have lagged behind the one dimensional counterpart. The single pixel camera built at Rice University and discussed by Wakin et. al. [5] has allowed algorithm research to go forward on compressive imaging but has not, as of yet, spurned new thoughts on application architectures in the same way as the Analog-to-Information community developed new sensors for wideband signals. We consider several Compressive imaging applications which offer fundamental improvements to current imaging sensors for target tracking and recognition.

Citation Download Citation

Robert Muise and Abhijit Mahalanobis "Compressive and adaptive imaging for target exploitation", Proc. SPIE 7442, Optics and Photonics for Information Processing III, 74420A (24 August 2009); https://doi.org/10.1117/12.832025

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KEYWORDS

Sensors

Compressive imaging

Video

Reconstruction algorithms

Detection and tracking algorithms

Multiplexing

Staring arrays

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