{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/single-image-haze-removal-using-conditional","title":"Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks","arxiv_id":"1903.00395","date":"2019-03-01","proceeding":null,"authors":["Joshua Peter Ebenezer","Bijaylaxmi Das","Sudipta Mukhopadhyay"],"abstract":"We present a method to restore a clear image from a haze-affected image using\na Wasserstein generative adversarial network. As the problem is\nill-conditioned, previous methods have required a prior on natural images or\nmultiple images of the same scene. We train a generative adversarial network to\nlearn the probability distribution of clear images conditioned on the\nhaze-affected images using the Wasserstein loss function, using a gradient\npenalty to enforce the Lipschitz constraint. The method is data-adaptive,\nend-to-end, and requires no further processing or tuning of parameters. We also\nincorporate the use of a texture-based loss metric and the L1 loss to improve\nresults, and show that our results are better than the current\nstate-of-the-art.","url_abs":"http://arxiv.org/abs/1903.00395v1","url_pdf":"http://arxiv.org/pdf/1903.00395v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"single-image-haze-removal-using-conditional","repo_url":"https://github.com/JoshuaEbenezer/cwgan","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":null,"task_name":"Generative Adversarial Network"},{"task_slug":"image-dehazing","task_name":"Image Dehazing"},{"task_slug":"single-image-haze-removal","task_name":"Single Image Haze Removal"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1903.00395","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}