{"title":"基于时间相干算法的视频级双目色调映射框架","authors":"Mingyue Feng, M. Loew","doi":"10.1109/AIPR.2017.8457950","DOIUrl":null,"url":null,"abstract":"A binocular tone-mapping framework can generate a binocular low-dynamic range (LDR) image pair that preserves more human-perceivable visual contents than a single LDR image. In this paper, to solve the temporal coherency problem when extending from this image-level system to a video-level system, we proposed a new binocular framework that integrates the existing image-level framework and the temporal coherency algorithm. The experimental data show that this proposed new framework can effectively solve the temporal coherency problem and generate binocular LDR videos without disturbing effects.","PeriodicalId":128779,"journal":{"name":"2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Video-Level Binocular Tone-mapping Framework Based on Temporal Coherency Algorithm\",\"authors\":\"Mingyue Feng, M. Loew\",\"doi\":\"10.1109/AIPR.2017.8457950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A binocular tone-mapping framework can generate a binocular low-dynamic range (LDR) image pair that preserves more human-perceivable visual contents than a single LDR image. In this paper, to solve the temporal coherency problem when extending from this image-level system to a video-level system, we proposed a new binocular framework that integrates the existing image-level framework and the temporal coherency algorithm. The experimental data show that this proposed new framework can effectively solve the temporal coherency problem and generate binocular LDR videos without disturbing effects.\",\"PeriodicalId\":128779,\"journal\":{\"name\":\"2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIPR.2017.8457950\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2017.8457950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video-Level Binocular Tone-mapping Framework Based on Temporal Coherency Algorithm
A binocular tone-mapping framework can generate a binocular low-dynamic range (LDR) image pair that preserves more human-perceivable visual contents than a single LDR image. In this paper, to solve the temporal coherency problem when extending from this image-level system to a video-level system, we proposed a new binocular framework that integrates the existing image-level framework and the temporal coherency algorithm. The experimental data show that this proposed new framework can effectively solve the temporal coherency problem and generate binocular LDR videos without disturbing effects.