Bayesian sparse reconstruction based on dictionary learning

Yan Wang; Jun Ke

doi:10.1117/12.2575180

10 October 2020 Bayesian sparse reconstruction based on dictionary learning

Yan Wang, Jun Ke

Proceedings Volume 11549, Advanced Optical Imaging Technologies III; 115491L (2020) https://doi.org/10.1117/12.2575180
Event: SPIE/COS Photonics Asia, 2020, Online Only

Conference Poster

Abstract

Imaging through thick scattering media produces a random speckle signal with wealth information, which can be restored by subsequent processing. While a moving target is hard to reconstruct by existing technology, we apply temporal Bayesian compressed sensing method to overcome this limitation. In addition, an over completed dictionary is used as a sparse base to improve the accuracy of the reconstructions. In this letter, we improve system time resolution without changing its spatial resolution and reconstruct T frame speckle images from a single temporal compressed speckle measurement.

Conference Presentation

Citation Download Citation

Yan Wang and Jun Ke "Bayesian sparse reconstruction based on dictionary learning", Proc. SPIE 11549, Advanced Optical Imaging Technologies III, 115491L (10 October 2020); https://doi.org/10.1117/12.2575180

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