{"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}
引用次数: 1
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.