{"title":"单幅图像去雾方法的不同雾霾图像条件","authors":"Noor Asma Husain, M. Rahim, Huma Chaudhry","doi":"10.1109/SSCI50451.2021.9659889","DOIUrl":null,"url":null,"abstract":"The dust, mist, haze, and smokiness of the atmosphere typically degrade images from the light and absorption. These effects have poor visibility, dimmed luminosity, low contrast, and distortion of colour. As a result, restoring a degraded image is difficult, especially in hazy conditions. The image dehazing method focuses on improving the visibility of image details while preserving image colours without causing data loss. Many image dehazing methods achieve the goal of removing haze while also addressing other issues such as oversaturation, colour distortion, and halo artefacts. However, the limitation of haze level rendered these approaches ineffective. A volume of various haze level data is required to demonstrate the efficiency of the image dehazing method in removing haze at all haze levels and obtaining the image's quality. This paper introduced a dynamic scattering coefficient to the dehazing algorithm for determining an applicable visibility range for different haze conditions. These proposed methods improve on the current state-of-the-art dehazing method in terms of image quality measurement results.","PeriodicalId":255763,"journal":{"name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Different Haze Image Conditions for Single Image Dehazing Method\",\"authors\":\"Noor Asma Husain, M. Rahim, Huma Chaudhry\",\"doi\":\"10.1109/SSCI50451.2021.9659889\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The dust, mist, haze, and smokiness of the atmosphere typically degrade images from the light and absorption. These effects have poor visibility, dimmed luminosity, low contrast, and distortion of colour. As a result, restoring a degraded image is difficult, especially in hazy conditions. The image dehazing method focuses on improving the visibility of image details while preserving image colours without causing data loss. Many image dehazing methods achieve the goal of removing haze while also addressing other issues such as oversaturation, colour distortion, and halo artefacts. However, the limitation of haze level rendered these approaches ineffective. A volume of various haze level data is required to demonstrate the efficiency of the image dehazing method in removing haze at all haze levels and obtaining the image's quality. This paper introduced a dynamic scattering coefficient to the dehazing algorithm for determining an applicable visibility range for different haze conditions. These proposed methods improve on the current state-of-the-art dehazing method in terms of image quality measurement results.\",\"PeriodicalId\":255763,\"journal\":{\"name\":\"2021 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSCI50451.2021.9659889\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI50451.2021.9659889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Different Haze Image Conditions for Single Image Dehazing Method
The dust, mist, haze, and smokiness of the atmosphere typically degrade images from the light and absorption. These effects have poor visibility, dimmed luminosity, low contrast, and distortion of colour. As a result, restoring a degraded image is difficult, especially in hazy conditions. The image dehazing method focuses on improving the visibility of image details while preserving image colours without causing data loss. Many image dehazing methods achieve the goal of removing haze while also addressing other issues such as oversaturation, colour distortion, and halo artefacts. However, the limitation of haze level rendered these approaches ineffective. A volume of various haze level data is required to demonstrate the efficiency of the image dehazing method in removing haze at all haze levels and obtaining the image's quality. This paper introduced a dynamic scattering coefficient to the dehazing algorithm for determining an applicable visibility range for different haze conditions. These proposed methods improve on the current state-of-the-art dehazing method in terms of image quality measurement results.