{"title":"基于改进粒子群优化的视频编码块匹配运动估计技术","authors":"Deepak Singh","doi":"10.1109/ETI4.051663.2021.9619265","DOIUrl":null,"url":null,"abstract":"In video coding, the block matching based motion estimation (BMME) schemes by exploiting the uni-modal error surface is quite popular for easy implementation. Though, many real-world video sequences exhibit multiple local minima within the block search window. This research article proposes a pattern based modified particle swarm optimization approach for motion estimation (PMPSO-ME). The population-based evolutionary method; PSO ensures the global optimum solution and avoids trapping into local minima.The proposed technique is analyzed on JM 18.6 reference software of H.264/AVC platform. The proposed technique is evaluated for compared with the state-of-the-art approaches in terms of number of search points, encoding time complexity, Bjontegaard metrics etc.","PeriodicalId":129682,"journal":{"name":"2021 Emerging Trends in Industry 4.0 (ETI 4.0)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved Block Matching Motion Estimation Technique using Modified Particle Swarm Optimization in Video Coding\",\"authors\":\"Deepak Singh\",\"doi\":\"10.1109/ETI4.051663.2021.9619265\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In video coding, the block matching based motion estimation (BMME) schemes by exploiting the uni-modal error surface is quite popular for easy implementation. Though, many real-world video sequences exhibit multiple local minima within the block search window. This research article proposes a pattern based modified particle swarm optimization approach for motion estimation (PMPSO-ME). The population-based evolutionary method; PSO ensures the global optimum solution and avoids trapping into local minima.The proposed technique is analyzed on JM 18.6 reference software of H.264/AVC platform. The proposed technique is evaluated for compared with the state-of-the-art approaches in terms of number of search points, encoding time complexity, Bjontegaard metrics etc.\",\"PeriodicalId\":129682,\"journal\":{\"name\":\"2021 Emerging Trends in Industry 4.0 (ETI 4.0)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Emerging Trends in Industry 4.0 (ETI 4.0)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETI4.051663.2021.9619265\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Emerging Trends in Industry 4.0 (ETI 4.0)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETI4.051663.2021.9619265","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved Block Matching Motion Estimation Technique using Modified Particle Swarm Optimization in Video Coding
In video coding, the block matching based motion estimation (BMME) schemes by exploiting the uni-modal error surface is quite popular for easy implementation. Though, many real-world video sequences exhibit multiple local minima within the block search window. This research article proposes a pattern based modified particle swarm optimization approach for motion estimation (PMPSO-ME). The population-based evolutionary method; PSO ensures the global optimum solution and avoids trapping into local minima.The proposed technique is analyzed on JM 18.6 reference software of H.264/AVC platform. The proposed technique is evaluated for compared with the state-of-the-art approaches in terms of number of search points, encoding time complexity, Bjontegaard metrics etc.