dc.contributor.author | Uddin, Mohammad Shorif | |
dc.contributor.author | Gautam, Bishal | |
dc.contributor.author | Sarker, Aditi | |
dc.contributor.author | Akter, Morium | |
dc.contributor.author | Haque, Mohammad Reduanul | |
dc.date.accessioned | 2019-05-16T06:35:53Z | |
dc.date.available | 2019-05-16T06:35:53Z | |
dc.date.issued | 2018-02-12 | |
dc.identifier.issn | 2572-7621 | |
dc.identifier.uri | http://hdl.handle.net/123456789/68 | |
dc.description.abstract | Haze, fog, rain usually hampered the performance of vision systems. So, removal of haze appearance in a scene should be the first priority for clear vision. Previously a dehazing mechanism was developed based on dark channel prior which cannot automatically set the patch size and the sky-region's transmission value. The current paper tries to fill this gap to automate these values. Experimentation has been conducted to find the performance on the basis of subjective as well as objective metrics. We have obtained satisfactory results compared to the existing techniques. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | IEEE | en_US |
dc.subject | image colour analysis | en_US |
dc.subject | image enhancement | en_US |
dc.subject | image restoration | en_US |
dc.title | Image-based automated haze removal using dark channel prior | en_US |
dc.type | Other | en_US |