Parallel hybrid bispectrum-multi-frame blind deconvolution image reconstruction technique
| Autor: | Allan Struther, Solmaz Hajmohammadi, Jeremy P. Bos, Saeid Nooshabadi, Glen Archer |
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| Rok vydání: | 2016 |
| Předmět: |
Blind deconvolution
Computer science Image quality business.industry Ensemble averaging ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering 02 engineering and technology Iterative reconstruction Hybrid algorithm Parallel processing (DSP implementation) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Speckle imaging Artificial intelligence business Bispectrum Information Systems |
| Zdroj: | Journal of Real-Time Image Processing. 16:919-929 |
| ISSN: | 1861-8219 1861-8200 |
| DOI: | 10.1007/s11554-016-0577-z |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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