Abstract
This paper presents B-MFBD, a parallel hybrid of bispectrum speckle imaging (SI) and multi-frame blind deconvolution (MFBD) image reconstruction techniques for anisoplanatic, long horizontal path imaging. Our aim is to recover an enhanced version of a turbulence-corrupted image by massive parallelization of an SI and MFBD algorithms. The bispectrum SI technique is used in place of the multi-frame ensemble averaging to initialize the iterative parallel MFBD algorithm. B-MFBD technique, through massive parallelization, provides significantly large improvement in execution speed to both the bispectrum SI and MFBD parts of the hybrid algorithm. We report \(85\,\%\) improvement in processing time with respect to the sequential implementation of the same algorithm for a \(256 \times 256\), gray-scale image, with comparable improvement in image quality.
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Notes
A is binary aperture function which is 1 in the aperture and 0 outside the aperture.
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Hajmohammadi, S., Nooshabadi, S., Archer, G.E. et al. Parallel hybrid bispectrum-multi-frame blind deconvolution image reconstruction technique. J Real-Time Image Proc 16, 919–929 (2019). https://doi.org/10.1007/s11554-016-0577-z
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DOI: https://doi.org/10.1007/s11554-016-0577-z