Digital Repository

Robust Single Image Dehazing and Image Enhancement via Generative Adversarial Networks

Show simple item record

dc.contributor.author Hilal, Ashfaaq
dc.date.accessioned 2024-04-05T09:57:11Z
dc.date.available 2024-04-05T09:57:11Z
dc.date.issued 2023
dc.identifier.citation Hilal, Ashfaaq (2023) Robust Single Image Dehazing and Image Enhancement via Generative Adversarial Networks. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2019394
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1999
dc.description.abstract Haze removal is an essential factor where various research communities related to computer vision have conducted research with explicit outputs. Image de-hazing consumes more time, and the state-of-the-art solutions are less robust. In order to achieve this, a GAN-based approach is likely to be used, where de-hazing is performed unanimously and then retainment of the image is done accordingly. en_US
dc.language.iso en en_US
dc.subject Image de-hazing en_US
dc.subject Generative Adversarial Network en_US
dc.subject CCTV en_US
dc.subject Image retainment en_US
dc.title Robust Single Image Dehazing and Image Enhancement via Generative Adversarial Networks en_US
dc.type Thesis en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search


Advanced Search

Browse

My Account