Mingchao Sun, Bao Zhang, Jinghong Liu, Yongyang Wang, Quan Yang
{"title":"航空红外和可见光图像的配准","authors":"Mingchao Sun, Bao Zhang, Jinghong Liu, Yongyang Wang, Quan Yang","doi":"10.1109/ICEIT.2010.5607665","DOIUrl":null,"url":null,"abstract":"In order to solve the registration problem of different source image existed on aerial image fusion, algorithms based on Particle Swarm Optimization (PSO) are applied as search strategy in this paper, and Alignment Metric (AM) is used as judgment. This study has realized the different source image registration of infrared and visible light with high speed, high accuracy and high reliability. Basically, with little restriction of gray level properties, a new alignment measure is applied, which can efficiently measure the image registration extent and tolerate noise well. Even more, the intelligent optimization algorithm - Particle Swarm Optimization (PSO) is combined to improve the registration precision and rate of infrared and visible light. Experimental results indicate that, the study attains the registration accuracy of pixel level, and every registration time is cut down over 40 percent compared to traditional method. The match algorithm based on AM, solves the registration problem that greater differences between different source images are existed on gray and characteristic. At the same time, the adoption of combining the intelligent optimization algorithms significantly improves the searching efficiency and convergence speed of the algorithms, and the registration result has higher accuracy and stability, which builds up solid foundation for different source image fusion. The method in this paper has a magnificent effect, and is easy for application and very suitable for engineering use.","PeriodicalId":346498,"journal":{"name":"2010 International Conference on Educational and Information Technology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"The registration of aerial infrared and visible images\",\"authors\":\"Mingchao Sun, Bao Zhang, Jinghong Liu, Yongyang Wang, Quan Yang\",\"doi\":\"10.1109/ICEIT.2010.5607665\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the registration problem of different source image existed on aerial image fusion, algorithms based on Particle Swarm Optimization (PSO) are applied as search strategy in this paper, and Alignment Metric (AM) is used as judgment. This study has realized the different source image registration of infrared and visible light with high speed, high accuracy and high reliability. Basically, with little restriction of gray level properties, a new alignment measure is applied, which can efficiently measure the image registration extent and tolerate noise well. Even more, the intelligent optimization algorithm - Particle Swarm Optimization (PSO) is combined to improve the registration precision and rate of infrared and visible light. Experimental results indicate that, the study attains the registration accuracy of pixel level, and every registration time is cut down over 40 percent compared to traditional method. The match algorithm based on AM, solves the registration problem that greater differences between different source images are existed on gray and characteristic. At the same time, the adoption of combining the intelligent optimization algorithms significantly improves the searching efficiency and convergence speed of the algorithms, and the registration result has higher accuracy and stability, which builds up solid foundation for different source image fusion. The method in this paper has a magnificent effect, and is easy for application and very suitable for engineering use.\",\"PeriodicalId\":346498,\"journal\":{\"name\":\"2010 International Conference on Educational and Information Technology\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Educational and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEIT.2010.5607665\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Educational and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEIT.2010.5607665","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The registration of aerial infrared and visible images
In order to solve the registration problem of different source image existed on aerial image fusion, algorithms based on Particle Swarm Optimization (PSO) are applied as search strategy in this paper, and Alignment Metric (AM) is used as judgment. This study has realized the different source image registration of infrared and visible light with high speed, high accuracy and high reliability. Basically, with little restriction of gray level properties, a new alignment measure is applied, which can efficiently measure the image registration extent and tolerate noise well. Even more, the intelligent optimization algorithm - Particle Swarm Optimization (PSO) is combined to improve the registration precision and rate of infrared and visible light. Experimental results indicate that, the study attains the registration accuracy of pixel level, and every registration time is cut down over 40 percent compared to traditional method. The match algorithm based on AM, solves the registration problem that greater differences between different source images are existed on gray and characteristic. At the same time, the adoption of combining the intelligent optimization algorithms significantly improves the searching efficiency and convergence speed of the algorithms, and the registration result has higher accuracy and stability, which builds up solid foundation for different source image fusion. The method in this paper has a magnificent effect, and is easy for application and very suitable for engineering use.