Fast algorithms for model-based imaging through turbulence

Venkatesh Sridhar; Sherman J. Kisner; Samuel P. Midkiff; Charles A. Bouman

doi:10.1117/12.2570789

20 September 2020 Fast algorithms for model-based imaging through turbulence

Venkatesh Sridhar, Sherman J. Kisner, Samuel P. Midkiff, Charles A. Bouman

Proceedings Volume 11543, Artificial Intelligence and Machine Learning in Defense Applications II; 1154304 (2020) https://doi.org/10.1117/12.2570789
Event: SPIE Security + Defence, 2020, Online Only

Abstract

Digital holography (DH) systems have the potential to perform single-shot imaging through deep turbulence by incorporating emerging algorithms, such as model-based iterative reconstruction (MBIR), that jointly estimate both the phase-errors and speckle-free image. However, the high computational cost of MBIR poses a challenge for use in practical applications. In this paper, we propose a method that makes MBIR feasible for real-time DH systems. Our method uses surrogate optimization techniques to simplify and speed up the reflectance and phase-error updates in MBIR. Further, our method accelerates computation of the surrogate-updates by leveraging cache-prefetching and SIMD vector processing units on each CPU core. We analyze the convergence and real CPU time of our method using simulated data sets, and demonstrate its dramatic speedup over the original MBIR approach.

Conference Presentation

Citation Download Citation

Venkatesh Sridhar, Sherman J. Kisner, Samuel P. Midkiff, and Charles A. Bouman "Fast algorithms for model-based imaging through turbulence", Proc. SPIE 11543, Artificial Intelligence and Machine Learning in Defense Applications II, 1154304 (20 September 2020); https://doi.org/10.1117/12.2570789

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