8 September 2011 Code aperture optimization for spectrally agile compressive imaging
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Abstract
Coded aperture spectral imaging (CASSI) provides a mechanism to capture a 3D spectral cube with a single shot 2D measurement. This paper extends the concept of CASSI to a system admitting multiple shot measurements which leads not only to higher quality of reconstruction, but also to spectrally selective imaging when the sequence of code aperture patterns is optimized. The aperture code optimization problem is shown to be analogous to the optimization of a constrained, multichannel filter bank. The optimal code apertures allow the decomposition of the CASSI measurements into several matrices, each having compressive information from only a few selected spectral bands. Each matrix is reconstructed separately and the results are merged if the full data cube is needed. This technique is equivalent to a filter bank decomposition of the CASSI measurements. The approach shows better quality and higher speed of reconstruction than a non-optimized multishot CASSI system. A number of simulations are developed to illustrate the spectral imaging characteristics attained by optimal aperture codes.
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Henry Arguello, Gonzalo R. Arce, "Code aperture optimization for spectrally agile compressive imaging", Proc. SPIE 8165, Unconventional Imaging, Wavefront Sensing, and Adaptive Coded Aperture Imaging and Non-Imaging Sensor Systems, 81651B (8 September 2011); doi: 10.1117/12.893590; https://doi.org/10.1117/12.893590
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