Robustness of speckle-imaging techniques applied to horizontal imaging scenarios

Bos, Jeremy P.

doi:10.1117/1.oe.51.8.083201

Cited by 19 publications

(12 citation statements)

References 29 publications

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“…For a given m Â n original image I and reconstructed image I 0 , the variable PSNR computed as PSNR ¼ 10:log 10 MAX 2 I MSE ð18Þ…”

Section: Resultsmentioning

confidence: 99%

“…The use of H LE here is limited to horizontal imaging where the acquisition takes places over a long horizontal paths. We have found the long-exposure OTF is the best choice in these scenarios [10].…”

Section: Bispectrum Speckle Imaging Techniquementioning

confidence: 99%

“…Equation (14) presents multiple paths for the estimation of the object phase at each spatial frequency. To have a reasonable signal to noise ratio (SNR) averaging over five different subplane choices (represented by the value of Df) is sufficient to provide a good balance between execution time and reconstructed image quality for daytime horizontal imaging [10].…”

Section: Bispectrum Speckle Imaging Techniquementioning

confidence: 99%

“…This allows replacing the convolution operations in spatial domain in Eqs. (6) and (10)(11) with the sequence of three operations viz. 2-D FFT, matrix-matrix multiplication, and 2-D IFFT.…”

Section: Parallelization Of Multi-frame Blind Deconvolutionmentioning

confidence: 99%

“…Similarly, Algorithm 4 presents the parallel implementation of Eqs. (10)(11). For each frame all operations, including summation, multiplication, 2-D FFT/ IFFT and exponentiation, are performed pixel-parallel on the GPU.…”

Section: Parallelization Of Multi-frame Blind Deconvolutionmentioning

confidence: 99%

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

Hajmohammadi

Nooshabadi

Archer

et al. 2016

J Real-Time Image Proc

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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 aimis 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 Â 256, gray-scale image, with comparable improvement in image quality.

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“…For a given m Â n original image I and reconstructed image I 0 , the variable PSNR computed as PSNR ¼ 10:log 10 MAX 2 I MSE ð18Þ…”

Section: Resultsmentioning

confidence: 99%

Section: Bispectrum Speckle Imaging Techniquementioning

confidence: 99%

Section: Bispectrum Speckle Imaging Techniquementioning

confidence: 99%

“…This allows replacing the convolution operations in spatial domain in Eqs. (6) and (10)(11) with the sequence of three operations viz. 2-D FFT, matrix-matrix multiplication, and 2-D IFFT.…”

Section: Parallelization Of Multi-frame Blind Deconvolutionmentioning

confidence: 99%

Section: Parallelization Of Multi-frame Blind Deconvolutionmentioning

confidence: 99%

See 3 more Smart Citations