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3 January 2020 Parallel optimization of O (1) rectangular kernel max/min filters algorithm
Tao Hu, Quanyi Chen, Xianyi Ren, Changwei Wang
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Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 1137330 (2020) https://doi.org/10.1117/12.2557699
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China
Abstract
The max/min filters are the most basic operator in gray-scale morphology. van Herk proposed an efficient O(1) rectangular kernel max/min filters algorithm which is independent of the size of filter window. This paper mainly studies the parallel optimization of van Herk’s max/min filters algorithm by using the single-instruction, multiple data (SIMD) technology and OpenMP parallel optimization technology for multi-core processors. First, the Intel Sreaming SIMD Extensions 2 (SSE2) is used to perform data-level parallel optimization for van Herk’s max/min filters algorithm in column direction, and a method based on histogram statistics is proposed to accelerate the calculation in row direction, the parallel speed-up ratio can reach 2. Then, the OpenMP parallel optimization technology is used to further perform thread-level parallel optimization for the SSE2 optimized version. The total speedup ratio under 4 cores and 4 threads CPU is about 7. Finally, compared with the rectangular kernel gray morphological operators in the powerful machine vision software MVTec HALCON17.12, the optimized algorithm in this paper has a great advantage in large window filtering size.
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Tao Hu, Quanyi Chen, Xianyi Ren, and Changwei Wang "Parallel optimization of O (1) rectangular kernel max/min filters algorithm", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137330 (3 January 2020); https://doi.org/10.1117/12.2557699
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KEYWORDS
Optimization (mathematics)
Image filtering
Algorithms
Parallel computing
Data conversion
Image processing
Data processing
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