{"title":"实现雾霾去除算法,增强弱光图像","authors":"K. Maheswari, Kadapa R. Charan","doi":"10.26634/jip.9.2.18796","DOIUrl":null,"url":null,"abstract":"The image is captured in foggy atmospheric conditions, resulting in hazy, visually degraded visibility; it obscures image quality. Instead of producing clear images, pixel-based metrics are not guaranteed. This updated image is used as input in computer vision for low-level tasks like segmentation. To improve this, it introduces a new approach to de-hazing an image, the end-to-end approach, to keep the visual quality of the generated images. So, it takes one step further to explore the possibility of using the network to perform a semantic segmentation method with U-Net. U-Net will be built and used in this model to improve the quality of the output even more.","PeriodicalId":292215,"journal":{"name":"i-manager’s Journal on Image Processing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Implementation of haze removal algorithm to enhance low light images\",\"authors\":\"K. Maheswari, Kadapa R. Charan\",\"doi\":\"10.26634/jip.9.2.18796\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The image is captured in foggy atmospheric conditions, resulting in hazy, visually degraded visibility; it obscures image quality. Instead of producing clear images, pixel-based metrics are not guaranteed. This updated image is used as input in computer vision for low-level tasks like segmentation. To improve this, it introduces a new approach to de-hazing an image, the end-to-end approach, to keep the visual quality of the generated images. So, it takes one step further to explore the possibility of using the network to perform a semantic segmentation method with U-Net. U-Net will be built and used in this model to improve the quality of the output even more.\",\"PeriodicalId\":292215,\"journal\":{\"name\":\"i-manager’s Journal on Image Processing\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"i-manager’s Journal on Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26634/jip.9.2.18796\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"i-manager’s Journal on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26634/jip.9.2.18796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of haze removal algorithm to enhance low light images
The image is captured in foggy atmospheric conditions, resulting in hazy, visually degraded visibility; it obscures image quality. Instead of producing clear images, pixel-based metrics are not guaranteed. This updated image is used as input in computer vision for low-level tasks like segmentation. To improve this, it introduces a new approach to de-hazing an image, the end-to-end approach, to keep the visual quality of the generated images. So, it takes one step further to explore the possibility of using the network to perform a semantic segmentation method with U-Net. U-Net will be built and used in this model to improve the quality of the output even more.