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Proceedings Paper

Multi-shot compressed coded aperture imaging
Author(s): Xiaopeng Shao; Juan Du; Tengfei Wu; Zhenhua Jin
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Paper Abstract

The classical methods of compressed coded aperture (CCA) still require an optical sensor with high resolution, although the sampling rate has broken the Nyquist sampling rate already. A novel architecture of multi-shot compressed coded aperture imaging (MCCAI) using a low resolution optical sensor is proposed, which is mainly based on the 4-f imaging system, combining with two spatial light modulators (SLM) to achieve the compressive imaging goal. The first SLM employed for random convolution is placed at the frequency spectrum plane of the 4-f imaging system, while the second SLM worked as a selecting filter is positioned in front of the optical sensor. By altering the random coded pattern of the second SLM and sampling, a couple of observations can be obtained by a low resolution optical sensor easily, and these observations will be combined mathematically and used to reconstruct the high resolution image. That is to say, MCCAI aims at realizing the super resolution imaging with multiple random samplings by using a low resolution optical sensor. To improve the computational imaging performance, total variation (TV) regularization is introduced into the super resolution reconstruction model to get rid of the artifacts, and alternating direction method of multipliers (ADM) is utilized to solve the optimal result efficiently. The results show that the MCCAI architecture is suitable for super resolution computational imaging using a much lower resolution optical sensor than traditional CCA imaging methods by capturing multiple frame images.

Paper Details

Date Published: 17 September 2013
PDF: 10 pages
Proc. SPIE 8877, Unconventional Imaging and Wavefront Sensing 2013, 887708 (17 September 2013); doi: 10.1117/12.2023212
Show Author Affiliations
Xiaopeng Shao, Xidian Univ. (China)
Juan Du, Xidian Univ. (China)
Tengfei Wu, Xidian Univ. (China)
Zhenhua Jin, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 8877:
Unconventional Imaging and Wavefront Sensing 2013
Jean J. Dolne; Thomas J. Karr; Victor L. Gamiz, Editor(s)

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