{"title":"利用图像处理方法补偿红外相机的光源尺寸效应","authors":"S. Schramm, R. Schmoll, A. Kroll","doi":"10.1109/ICST46873.2019.9047669","DOIUrl":null,"url":null,"abstract":"While many infrared camera-specific properties are considered for practical application, the influence of the radiation distribution surrounding the measuring spot is often neglected for thermal cameras. However, this has a significant influence on the uncertainty of thermal imaging cameras when measuring absolute temperatures, referred to as the size-of-source effect. Since thermal cameras acquire information about the radiation distribution around a potential point of interest through their spatially resolved measurement, neighborhood pixels could be used to reduce the uncertainty. In this paper, a convolution filter is presented whose parameters are optimized with regard to the compensation of the size-of-source effect for two different infrared cameras. The results show that the filter can reduce the effect significantly for different object geometries or even at the border of a thermal image. The algorithm could be applied to infrared cameras as a post-processing step in the future.","PeriodicalId":344937,"journal":{"name":"2019 13th International Conference on Sensing Technology (ICST)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Compensation of the Size-of-Source Effect of Infrared Cameras Using Image Processing Methods\",\"authors\":\"S. Schramm, R. Schmoll, A. Kroll\",\"doi\":\"10.1109/ICST46873.2019.9047669\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While many infrared camera-specific properties are considered for practical application, the influence of the radiation distribution surrounding the measuring spot is often neglected for thermal cameras. However, this has a significant influence on the uncertainty of thermal imaging cameras when measuring absolute temperatures, referred to as the size-of-source effect. Since thermal cameras acquire information about the radiation distribution around a potential point of interest through their spatially resolved measurement, neighborhood pixels could be used to reduce the uncertainty. In this paper, a convolution filter is presented whose parameters are optimized with regard to the compensation of the size-of-source effect for two different infrared cameras. The results show that the filter can reduce the effect significantly for different object geometries or even at the border of a thermal image. The algorithm could be applied to infrared cameras as a post-processing step in the future.\",\"PeriodicalId\":344937,\"journal\":{\"name\":\"2019 13th International Conference on Sensing Technology (ICST)\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 13th International Conference on Sensing Technology (ICST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICST46873.2019.9047669\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 13th International Conference on Sensing Technology (ICST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICST46873.2019.9047669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compensation of the Size-of-Source Effect of Infrared Cameras Using Image Processing Methods
While many infrared camera-specific properties are considered for practical application, the influence of the radiation distribution surrounding the measuring spot is often neglected for thermal cameras. However, this has a significant influence on the uncertainty of thermal imaging cameras when measuring absolute temperatures, referred to as the size-of-source effect. Since thermal cameras acquire information about the radiation distribution around a potential point of interest through their spatially resolved measurement, neighborhood pixels could be used to reduce the uncertainty. In this paper, a convolution filter is presented whose parameters are optimized with regard to the compensation of the size-of-source effect for two different infrared cameras. The results show that the filter can reduce the effect significantly for different object geometries or even at the border of a thermal image. The algorithm could be applied to infrared cameras as a post-processing step in the future.