{"title":"用于夜间监视的照明和基于运动的视频增强","authors":"Jing Li, S.Z. Li, Q. Pan, Tao Yang","doi":"10.1109/VSPETS.2005.1570912","DOIUrl":null,"url":null,"abstract":"This work presents a context enhancement method of low illumination video for night surveillance. A unique characteristic of the algorithm is its ability to extract and maintenance the meaningful information like highlight area or moving objects with low contrast in the enhanced image, meanwhile recover the surrounding scene information by fusing the daytime background image. A main challenge comes from the extraction of meaningful area in the night video sequence. To address this problem, a novel bidirectional extraction approach is presented. In evaluation experiments with real data, the notable information of the night video is extracted successfully and the background scene is fused smoothly with the night images to show enhanced surveillance video for observers.","PeriodicalId":435841,"journal":{"name":"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"Illumination and motion-based video enhancement for night surveillance\",\"authors\":\"Jing Li, S.Z. Li, Q. Pan, Tao Yang\",\"doi\":\"10.1109/VSPETS.2005.1570912\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work presents a context enhancement method of low illumination video for night surveillance. A unique characteristic of the algorithm is its ability to extract and maintenance the meaningful information like highlight area or moving objects with low contrast in the enhanced image, meanwhile recover the surrounding scene information by fusing the daytime background image. A main challenge comes from the extraction of meaningful area in the night video sequence. To address this problem, a novel bidirectional extraction approach is presented. In evaluation experiments with real data, the notable information of the night video is extracted successfully and the background scene is fused smoothly with the night images to show enhanced surveillance video for observers.\",\"PeriodicalId\":435841,\"journal\":{\"name\":\"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance\",\"volume\":\"100 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VSPETS.2005.1570912\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VSPETS.2005.1570912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Illumination and motion-based video enhancement for night surveillance
This work presents a context enhancement method of low illumination video for night surveillance. A unique characteristic of the algorithm is its ability to extract and maintenance the meaningful information like highlight area or moving objects with low contrast in the enhanced image, meanwhile recover the surrounding scene information by fusing the daytime background image. A main challenge comes from the extraction of meaningful area in the night video sequence. To address this problem, a novel bidirectional extraction approach is presented. In evaluation experiments with real data, the notable information of the night video is extracted successfully and the background scene is fused smoothly with the night images to show enhanced surveillance video for observers.