超级像素算法SLIC的并行优化

2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS) Pub Date : 2022-07-22 DOI:10.1109/ISPDS56360.2022.9874224

Xiaoqi Luo, Yuanjie Xing, Senhai Xu

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引用次数: 1

摘要

超级像素算法SLIC采用K-means均值聚类方法有效生成超级像素。与其他超像素算法相比，该算法效率更高，提高了分割性能。为了进一步提高程序的性能，从编译优化、数据结构优化、循环向量化、OpenMP并行优化和算法优化五个主要方向对程序进行了优化。

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Parallel Optimization of Super Pixel Algorithm SLIC

Super pixel algorithm SLIC uses K-means mean clustering method to effectively generate super pixels. Compared with other super pixel algorithms, it is more efficient and improves the segmentation performance. In order to further improve its performance, the program is optimized from five major directions: compilation optimization, data structure optimization, loop vectorization, OpenMP parallel optimization and algorithm optimization.

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来源期刊

2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)

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