{"title":"超级像素算法SLIC的并行优化","authors":"Xiaoqi Luo, Yuanjie Xing, Senhai Xu","doi":"10.1109/ISPDS56360.2022.9874224","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":280244,"journal":{"name":"2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)","volume":"8 11","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Parallel Optimization of Super Pixel Algorithm SLIC\",\"authors\":\"Xiaoqi Luo, Yuanjie Xing, Senhai Xu\",\"doi\":\"10.1109/ISPDS56360.2022.9874224\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":280244,\"journal\":{\"name\":\"2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)\",\"volume\":\"8 11\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDS56360.2022.9874224\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPDS56360.2022.9874224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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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