{"title":"基于多尺度Retinex和ASIFT特征的变电站设备红外和可见光图像配准研究","authors":"Ning Yang, Yang Yang, Peng Li, Fei Gao","doi":"10.1117/12.2605000","DOIUrl":null,"url":null,"abstract":"Infrared and visible image registration of substation equipment is of great significance for power equipment detection and fault diagnosis. The scene of substation is complex, and the background of equipment image is usually messy, and the feature points of visible image are easy to fall on the background. The metal has good thermal conductivity, and its temperature is close to the ambient temperature. The metal part in the infrared image with metal tower as the background can not be clearly displayed, which is easy to cause the image mismatch or even unable to match. The existing registration methods such as SIFT, SURF and ASIFT are difficult to effectively solve this kind of image registration problem of substation equipment with complex background. To solve this problem, this paper proposes an infrared and visible image registration algorithm based on Multi-scale Retinex and ASIFT features. Firstly, the Multi-scale Retinex algorithm is used to separate the components representing the properties of the object in the visible image, so as to weaken the influence of the clutter background. Then, the ASIFT algorithm is used to do affine transformation to simulate the affine deformation under all parallax, and the feature points are roughly matched Finally, the random sampling consistent algorithm is added to eliminate the mismatching points. Experimental results show that the algorithm can increase the number of matching points by at least 4 times, the average matching accuracy is improved by 13%, and the average matching time is shortened by 183ms.","PeriodicalId":90079,"journal":{"name":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","volume":"1 1","pages":"1191303 - 1191303-8"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research on infrared and visible image registration of substation equipment based on multi-scale Retinex and ASIFT features\",\"authors\":\"Ning Yang, Yang Yang, Peng Li, Fei Gao\",\"doi\":\"10.1117/12.2605000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Infrared and visible image registration of substation equipment is of great significance for power equipment detection and fault diagnosis. The scene of substation is complex, and the background of equipment image is usually messy, and the feature points of visible image are easy to fall on the background. The metal has good thermal conductivity, and its temperature is close to the ambient temperature. The metal part in the infrared image with metal tower as the background can not be clearly displayed, which is easy to cause the image mismatch or even unable to match. The existing registration methods such as SIFT, SURF and ASIFT are difficult to effectively solve this kind of image registration problem of substation equipment with complex background. To solve this problem, this paper proposes an infrared and visible image registration algorithm based on Multi-scale Retinex and ASIFT features. Firstly, the Multi-scale Retinex algorithm is used to separate the components representing the properties of the object in the visible image, so as to weaken the influence of the clutter background. Then, the ASIFT algorithm is used to do affine transformation to simulate the affine deformation under all parallax, and the feature points are roughly matched Finally, the random sampling consistent algorithm is added to eliminate the mismatching points. Experimental results show that the algorithm can increase the number of matching points by at least 4 times, the average matching accuracy is improved by 13%, and the average matching time is shortened by 183ms.\",\"PeriodicalId\":90079,\"journal\":{\"name\":\"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging\",\"volume\":\"1 1\",\"pages\":\"1191303 - 1191303-8\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2605000\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"... International Workshop on Pattern Recognition in NeuroImaging. International Workshop on Pattern Recognition in NeuroImaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2605000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on infrared and visible image registration of substation equipment based on multi-scale Retinex and ASIFT features
Infrared and visible image registration of substation equipment is of great significance for power equipment detection and fault diagnosis. The scene of substation is complex, and the background of equipment image is usually messy, and the feature points of visible image are easy to fall on the background. The metal has good thermal conductivity, and its temperature is close to the ambient temperature. The metal part in the infrared image with metal tower as the background can not be clearly displayed, which is easy to cause the image mismatch or even unable to match. The existing registration methods such as SIFT, SURF and ASIFT are difficult to effectively solve this kind of image registration problem of substation equipment with complex background. To solve this problem, this paper proposes an infrared and visible image registration algorithm based on Multi-scale Retinex and ASIFT features. Firstly, the Multi-scale Retinex algorithm is used to separate the components representing the properties of the object in the visible image, so as to weaken the influence of the clutter background. Then, the ASIFT algorithm is used to do affine transformation to simulate the affine deformation under all parallax, and the feature points are roughly matched Finally, the random sampling consistent algorithm is added to eliminate the mismatching points. Experimental results show that the algorithm can increase the number of matching points by at least 4 times, the average matching accuracy is improved by 13%, and the average matching time is shortened by 183ms.