Massive parallel processing of image reconstruction from bispectrum through turbulence.

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Department of Electrical and Computer Engineering; Center for Scalable Architectures and Systems


This paper presents a massively parallel method for the phase reconstruction of an object from its bispectrum phase. Our aim is to recover an enhanced version of a turbulence-corrupted image by developing an efficient and fast parallel image-restoration algorithm. The proposed massively parallel bispectrum algorithm relies on multiple block parallelization. Further, in each block, we employ wavefront processing through strength reduction to parallelize an iterative algorithm. Results are presented and compared with the existing iterative bispectrum method. We report a speed-up factor of 85.94 with respect to sequential implementation of the same algorithm for an image size of 1024×1024.

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Applied Optics