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8 June 2012 Compressive imaging: exploiting multiple frames for enhanced video reconstruction
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Abstract
We consider a coded aperture imaging system which collects far fewer measurements than the underlying resolution of the scene we wish to exploit. Our sensing model considers an imaging system which subsamples pixels intensities with a Spatial Light Modulator (SLM) device. We present a general approach that can be applied to compressively sensed measurements gathered with respect to our sensing model, in order to improve reconstruction quality beyond a general reconstruction algorithm. The approach exploits capturing overlapping subsequent frames in a panning camera scene or capturing novel compressively sensed measurements of the static camera scene by utilizing dynamic aperture codes. We also consider the effects of projective distortions from various camera positions of subsequent frames within our approach. The result is a decrease in the effective compression rate of the system and therefore a significantly improved compressively sensed reconstruction. Results are presented for various reconstruction algorithms on natural, man-made, and mixed scenery of panning camera scenery as well as static camera scenery.
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Jonathan Tucker and Robert Muise "Compressive imaging: exploiting multiple frames for enhanced video reconstruction", Proc. SPIE 8365, Compressive Sensing, 83650K (8 June 2012); https://doi.org/10.1117/12.919688
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