{"title":"通过图像分解从图像中去除雪","authors":"D. Rajderkar, P. Mohod","doi":"10.1109/ICE-CCN.2013.6528565","DOIUrl":null,"url":null,"abstract":"Snowfall removal from an image is a challenging problem. In this paper, we propose a snowfall removal framework via image decomposition based on Morphological component analysis. The proposed methods first decompose an image into low frequency (LF) and high frequency (HF) parts using bilateral filter. The high frequency part is then decomposing into “snow component” and “non snow component” by performing dictionary learning and sparse coding.","PeriodicalId":286830,"journal":{"name":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Removing snow from an image via image decomposition\",\"authors\":\"D. Rajderkar, P. Mohod\",\"doi\":\"10.1109/ICE-CCN.2013.6528565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Snowfall removal from an image is a challenging problem. In this paper, we propose a snowfall removal framework via image decomposition based on Morphological component analysis. The proposed methods first decompose an image into low frequency (LF) and high frequency (HF) parts using bilateral filter. The high frequency part is then decomposing into “snow component” and “non snow component” by performing dictionary learning and sparse coding.\",\"PeriodicalId\":286830,\"journal\":{\"name\":\"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICE-CCN.2013.6528565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICE-CCN.2013.6528565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Removing snow from an image via image decomposition
Snowfall removal from an image is a challenging problem. In this paper, we propose a snowfall removal framework via image decomposition based on Morphological component analysis. The proposed methods first decompose an image into low frequency (LF) and high frequency (HF) parts using bilateral filter. The high frequency part is then decomposing into “snow component” and “non snow component” by performing dictionary learning and sparse coding.