Guillermo Machuca, S. Torres, Anselmo Jara, Laura A. Viafora, Pablo Gutiérrez
{"title":"Restoration and Digital Super-Resolution for Infrared Microscopy Imaging","authors":"Guillermo Machuca, S. Torres, Anselmo Jara, Laura A. Viafora, Pablo Gutiérrez","doi":"10.1145/3271553.3271607","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a unified method to reduce infrared optoelectronic imaging degradations and perform digital superresolution from a sequence of infrared microscopy images. The proposed method combines two regulators highlighting the spatial features of the scene, maintaining fine texture image details and better preserving sharp edges. Further, the method compensates the presence of fixed-pattern noise and used a deconvolution filter to reduce blurring. The method is implemented on a built-in mid-wave infrared microscopy imaging system. The results show a significant reduction in the imaging nonuniformity and blur, achieving better digital resolution identifying more details of the different scene object thermal patterns.","PeriodicalId":414782,"journal":{"name":"Proceedings of the 2nd International Conference on Vision, Image and Signal Processing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Conference on Vision, Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3271553.3271607","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose a unified method to reduce infrared optoelectronic imaging degradations and perform digital superresolution from a sequence of infrared microscopy images. The proposed method combines two regulators highlighting the spatial features of the scene, maintaining fine texture image details and better preserving sharp edges. Further, the method compensates the presence of fixed-pattern noise and used a deconvolution filter to reduce blurring. The method is implemented on a built-in mid-wave infrared microscopy imaging system. The results show a significant reduction in the imaging nonuniformity and blur, achieving better digital resolution identifying more details of the different scene object thermal patterns.