Solmaz Hajmohammadi, Saeid Nooshabadi, and Jeremy P. Bos, "Massive parallel processing of image reconstruction from bispectrum through turbulence," Appl. Opt. 54, 9370-9378 (2015)
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 .
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The experimentation platform is MATLAB, R2013b, 64-bit, on a six-core Intel Xeon CPU, X5650 2.67 GHz.
Table does not include the number of integer operations to compute 229,376,000 the indices into the 2D structure required for the bispectrum calculation.
Table 2.
Number of Complex Operations for Various Images Sizes for Complete Decomposition
INB-DP/INB-SP, interior blocks parallelized in double/single precision; INSDB-DP/INSDB-SP, interior and side blocks parallelized in double/single precision.
Table 4.
Computation Times (in Seconds) for Block Size of and Image Size of
INB-DP/INB-SP, interior blocks parallelized in double/single precision; INSDB-DP/INSDB-SP, interior and side blocks parallelized in double/single precision.
Table 5.
Execution Times (in Seconds) for Different Image Sizes
Parallel Algorithm
Image Size
Recursive Algorithm
Mem-Tx
Compute
Total
Speed- up
69.00
0.00
2.61
2.61
26.43
319.98
0.00
4.68
4.68
68.37
695.00
4.82
6.86
11.68
59.50
1360.50
5.90
9.93
15.83
85.94
Table 6.
Execution Times (in Seconds) for Different Numbers of Subplanes for the Image Size of
Number of subplanes
5
6
7
8
9
10
11
12
13
14
15
16
Timing
2.61
2.87
3.14
3.4
3.83
4.26
4.75
5.25
5.83
6.46
7.17
7.81
Tables (6)
Table 1.
Execution Times (in Seconds) and Approximate Number of Complex Operations for the Recursive Reconstruction of the 50 Frames of Image Sizea
The experimentation platform is MATLAB, R2013b, 64-bit, on a six-core Intel Xeon CPU, X5650 2.67 GHz.
Table does not include the number of integer operations to compute 229,376,000 the indices into the 2D structure required for the bispectrum calculation.
Table 2.
Number of Complex Operations for Various Images Sizes for Complete Decomposition
INB-DP/INB-SP, interior blocks parallelized in double/single precision; INSDB-DP/INSDB-SP, interior and side blocks parallelized in double/single precision.
Table 4.
Computation Times (in Seconds) for Block Size of and Image Size of
INB-DP/INB-SP, interior blocks parallelized in double/single precision; INSDB-DP/INSDB-SP, interior and side blocks parallelized in double/single precision.
Table 5.
Execution Times (in Seconds) for Different Image Sizes
Parallel Algorithm
Image Size
Recursive Algorithm
Mem-Tx
Compute
Total
Speed- up
69.00
0.00
2.61
2.61
26.43
319.98
0.00
4.68
4.68
68.37
695.00
4.82
6.86
11.68
59.50
1360.50
5.90
9.93
15.83
85.94
Table 6.
Execution Times (in Seconds) for Different Numbers of Subplanes for the Image Size of
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