Parallel hybrid bispectrum-multi-frame blind deconvolution image reconstruction technique

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 X 256, gray-scale image, with comparable improvement in image quality