{"title":"一种结合矩匹配和插值的红外图像去条纹新方法","authors":"Zhendong Gong, Hanbing Leng, Jianzhong Cao, Jihong Wang, Qingquan Wu, Xinming Fan, Bing Zhao, Lei Yang, Jiawen Liao","doi":"10.1109/ICIST.2014.6920504","DOIUrl":null,"url":null,"abstract":"Stripe noise is very common in uncooled infrared imaging systems and often severely degrades the image quality. Based on the analysis of existing methods, a new destriping method combining moment matching and interpolation was proposed. The method mainly consisted of three steps: Firstly, moment matching was used to eliminate most stripes. Then an adaptive algorithm was used to classify the left stripes into three types: one-pixel-width stripes, two-pixel-width stripes and local stripes. Finally, these left stripes were identified and removed with weighted multi-neighborhood interpolation. The algorithm was tested with IR images heavily polluted by stripe noises, and the result indicated that it could efficiently remove stripe noise and enhance the image quality significantly better than the single method discussed in literature.","PeriodicalId":306383,"journal":{"name":"2014 4th IEEE International Conference on Information Science and Technology","volume":"324 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A new destriping method combining moment matching and interpolation in infrared images\",\"authors\":\"Zhendong Gong, Hanbing Leng, Jianzhong Cao, Jihong Wang, Qingquan Wu, Xinming Fan, Bing Zhao, Lei Yang, Jiawen Liao\",\"doi\":\"10.1109/ICIST.2014.6920504\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stripe noise is very common in uncooled infrared imaging systems and often severely degrades the image quality. Based on the analysis of existing methods, a new destriping method combining moment matching and interpolation was proposed. The method mainly consisted of three steps: Firstly, moment matching was used to eliminate most stripes. Then an adaptive algorithm was used to classify the left stripes into three types: one-pixel-width stripes, two-pixel-width stripes and local stripes. Finally, these left stripes were identified and removed with weighted multi-neighborhood interpolation. The algorithm was tested with IR images heavily polluted by stripe noises, and the result indicated that it could efficiently remove stripe noise and enhance the image quality significantly better than the single method discussed in literature.\",\"PeriodicalId\":306383,\"journal\":{\"name\":\"2014 4th IEEE International Conference on Information Science and Technology\",\"volume\":\"324 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 4th IEEE International Conference on Information Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIST.2014.6920504\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 4th IEEE International Conference on Information Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIST.2014.6920504","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new destriping method combining moment matching and interpolation in infrared images
Stripe noise is very common in uncooled infrared imaging systems and often severely degrades the image quality. Based on the analysis of existing methods, a new destriping method combining moment matching and interpolation was proposed. The method mainly consisted of three steps: Firstly, moment matching was used to eliminate most stripes. Then an adaptive algorithm was used to classify the left stripes into three types: one-pixel-width stripes, two-pixel-width stripes and local stripes. Finally, these left stripes were identified and removed with weighted multi-neighborhood interpolation. The algorithm was tested with IR images heavily polluted by stripe noises, and the result indicated that it could efficiently remove stripe noise and enhance the image quality significantly better than the single method discussed in literature.