{"title":"基于小波变换的蚁群与粒子群混合算法图像配准","authors":"Aiye Shi, Fengchen Huang, Yang Pan, Lizhong Xu","doi":"10.1109/ICMV.2009.11","DOIUrl":null,"url":null,"abstract":"Mutual information based image registration has the advantages of high precision and strong robustness. However, the solution of this registration method is easy to fall into the local extremes. To overcome this problem, in this paper we propose a new optimal algorithm for image registration, which combines ant colony algorithm with particle swarm algorithm based on wavelet transform. Experiment results demonstrate our proposed approach effective.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Image Registration Using Ant Colony and Particle Swarm Hybrid Algorithm Based on Wavelet Transform\",\"authors\":\"Aiye Shi, Fengchen Huang, Yang Pan, Lizhong Xu\",\"doi\":\"10.1109/ICMV.2009.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mutual information based image registration has the advantages of high precision and strong robustness. However, the solution of this registration method is easy to fall into the local extremes. To overcome this problem, in this paper we propose a new optimal algorithm for image registration, which combines ant colony algorithm with particle swarm algorithm based on wavelet transform. Experiment results demonstrate our proposed approach effective.\",\"PeriodicalId\":315778,\"journal\":{\"name\":\"2009 Second International Conference on Machine Vision\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Second International Conference on Machine Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMV.2009.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Second International Conference on Machine Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMV.2009.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image Registration Using Ant Colony and Particle Swarm Hybrid Algorithm Based on Wavelet Transform
Mutual information based image registration has the advantages of high precision and strong robustness. However, the solution of this registration method is easy to fall into the local extremes. To overcome this problem, in this paper we propose a new optimal algorithm for image registration, which combines ant colony algorithm with particle swarm algorithm based on wavelet transform. Experiment results demonstrate our proposed approach effective.