基于截断总变分法的单雾图像去雾

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture Pub Date : 2020-10-15 DOI:10.1145/3421766.3421772

Yin Gao, Yijing Su, Jun Li

{"title":"基于截断总变分法的单雾图像去雾","authors":"Yin Gao, Yijing Su, Jun Li","doi":"10.1145/3421766.3421772","DOIUrl":null,"url":null,"abstract":"Existing dehazing methods are usually to appear visual problems. In the paper, we put forward a truncated total variation method (TTV) to eliminate haze. A histogram analysis is firstly developed to obtain global atmospheric light. Then, using an adaptive boundary constraint TTV to optimize the transmission properly. Finally, a new DCP is presented to remove haze. Shown in experimental results, our method can outperform existent methods on the visual effect.","PeriodicalId":360184,"journal":{"name":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Single Fog Image Dehazing via Truncated Total Variation Method\",\"authors\":\"Yin Gao, Yijing Su, Jun Li\",\"doi\":\"10.1145/3421766.3421772\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Existing dehazing methods are usually to appear visual problems. In the paper, we put forward a truncated total variation method (TTV) to eliminate haze. A histogram analysis is firstly developed to obtain global atmospheric light. Then, using an adaptive boundary constraint TTV to optimize the transmission properly. Finally, a new DCP is presented to remove haze. Shown in experimental results, our method can outperform existent methods on the visual effect.\",\"PeriodicalId\":360184,\"journal\":{\"name\":\"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3421766.3421772\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3421766.3421772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

现有的除雾方法通常会出现视觉问题。本文提出了一种截断总变分法(TTV)来消除雾霾。首先提出了一种直方图分析方法来获取全球大气光。然后，利用自适应边界约束TTV对传输进行优化。最后，提出了一种新的DCP来去除雾霾。实验结果表明，我们的方法在视觉效果上优于现有的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Single Fog Image Dehazing via Truncated Total Variation Method

Existing dehazing methods are usually to appear visual problems. In the paper, we put forward a truncated total variation method (TTV) to eliminate haze. A histogram analysis is firstly developed to obtain global atmospheric light. Then, using an adaptive boundary constraint TTV to optimize the transmission properly. Finally, a new DCP is presented to remove haze. Shown in experimental results, our method can outperform existent methods on the visual effect.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture

自引率

0.00%

发文量