{"title":"Feature Enhancement Using Gradient Salience on Thermal Image","authors":"Zelin Li, Jian Zhang, Qiang Wu, G. Geers","doi":"10.1109/DICTA.2010.99","DOIUrl":null,"url":null,"abstract":"Feature enhancement in an image is to reinforce some exacted features so that it can be used for object classification and detection. As the thermal image is lack of texture and colorful information, the techniques for visual image feature enhancement is insufficient to apply to thermal images. In this paper, we propose a new gradient-based approach for feature enhancement in thermal image. We use the statistical properties of gradient of foreground object profiles, and formulate object features with gradient saliency. Empirical evaluation of the proposed approach shows significant performance improved on human contours which can be used for detection and classification.","PeriodicalId":246460,"journal":{"name":"2010 International Conference on Digital Image Computing: Techniques and Applications","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Digital Image Computing: Techniques and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2010.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Feature enhancement in an image is to reinforce some exacted features so that it can be used for object classification and detection. As the thermal image is lack of texture and colorful information, the techniques for visual image feature enhancement is insufficient to apply to thermal images. In this paper, we propose a new gradient-based approach for feature enhancement in thermal image. We use the statistical properties of gradient of foreground object profiles, and formulate object features with gradient saliency. Empirical evaluation of the proposed approach shows significant performance improved on human contours which can be used for detection and classification.