{"title":"基于暗通道先验和逆图像的单幅图像去雾算法","authors":"Xiao Zhou, L. Bai, Chengyou Wang","doi":"10.5829/ije.2017.30.10a.07","DOIUrl":null,"url":null,"abstract":"The sky regions of foggy image processed by all the existing conventional dehazing methods are degraded by color distortion and severe noise. This paper proposes an improved algorithm which combines dark channel prior and inverse image. We first invert the foggy image, and then estimate the transmission of the inverse image. At last, compared with the non-inversed transmission, the larger values of the transmission are the final transmission. This algorithm tends to refine the medium transmission by adjusting the values of pixels in the bright region to meet the hypothesis of dark channel prior. The method is viable to eliminate color distortion of the dehazed image.","PeriodicalId":416886,"journal":{"name":"International journal of engineering. Transactions A: basics","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Single Image Dehazing Algorithm Based on Dark Channel Prior and Inverse Image\",\"authors\":\"Xiao Zhou, L. Bai, Chengyou Wang\",\"doi\":\"10.5829/ije.2017.30.10a.07\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The sky regions of foggy image processed by all the existing conventional dehazing methods are degraded by color distortion and severe noise. This paper proposes an improved algorithm which combines dark channel prior and inverse image. We first invert the foggy image, and then estimate the transmission of the inverse image. At last, compared with the non-inversed transmission, the larger values of the transmission are the final transmission. This algorithm tends to refine the medium transmission by adjusting the values of pixels in the bright region to meet the hypothesis of dark channel prior. The method is viable to eliminate color distortion of the dehazed image.\",\"PeriodicalId\":416886,\"journal\":{\"name\":\"International journal of engineering. Transactions A: basics\",\"volume\":\"110 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of engineering. Transactions A: basics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5829/ije.2017.30.10a.07\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of engineering. Transactions A: basics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5829/ije.2017.30.10a.07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Single Image Dehazing Algorithm Based on Dark Channel Prior and Inverse Image
The sky regions of foggy image processed by all the existing conventional dehazing methods are degraded by color distortion and severe noise. This paper proposes an improved algorithm which combines dark channel prior and inverse image. We first invert the foggy image, and then estimate the transmission of the inverse image. At last, compared with the non-inversed transmission, the larger values of the transmission are the final transmission. This algorithm tends to refine the medium transmission by adjusting the values of pixels in the bright region to meet the hypothesis of dark channel prior. The method is viable to eliminate color distortion of the dehazed image.