Publication:
Real-Time Video Enhancement for Various Weather Conditions Using Dark Channel and Fuzzy Logic

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dc.ConferencecodeUniv Teknologi Petronas, IEEE
dc.ConferencedateJUN 03-05, 2014
dc.ConferencelocationMALAYSIA
dc.ConferencenameInternational Conference on Computer and Information Sciences (ICCOINS)
dc.contributor.authorAlajarmeh, Aen_US
dc.contributor.authorSalam, RAen_US
dc.contributor.authorMarhusin, MFen_US
dc.contributor.authorAbdulrahim, Ken_US
dc.date.accessioned2024-05-29T02:49:52Z
dc.date.available2024-05-29T02:49:52Z
dc.date.issued2014
dc.description.abstractRain, fog and haze are natural phenomena that fade scenes, limit the visibility range, and cause shifts in colors. These phenomena also play a decisive role in determining the degree of reliability of many kinds of outdoor applications, such as aerial and satellite imaging, surveillance, and driver assistance systems. Thus, removing their effects from images/videos is very crucial. Due to its mathematically ill posed nature, enhancement process of rain, fog, and haze plagued images/videos is highly challenging. In this paper, we propose a fast yet robust technique to enhance the visibility of video frames using the dark channel prior combined with fuzzy logic-based technique. The dark channel prior is a statistical regularity of outdoor haze-free images based on the observation that most local patches in the haze-free images contain pixels which are dark in at least one color channel, where the fuzzy logic-based technique is used to map an input space to an output space using a collection of fuzzy membership functions and rules to decide softly in case of uncertainties. The combination of the dark channel and the fuzzy logic-based technique will produce high quality haze-free images in real-time. Furthermore, it will be combined with rules derived from the stable atmospheric scattering model and will yield a fast yet high quality enhancement results.
dc.identifier.scopusWOS:000347892600005
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/10954
dc.languageEnglish
dc.language.isoen_US
dc.publisherIEEEen_US
dc.relation.ispartof2014 International Conference On Computer And Information Sciences (Iccoins)
dc.sourceWeb Of Science (ISI)
dc.subjectairlighten_US
dc.subjectdark channelen_US
dc.subjectfuzzy logicen_US
dc.subjectreal-time applicationsen_US
dc.titleReal-Time Video Enhancement for Various Weather Conditions Using Dark Channel and Fuzzy Logic
dc.typeProceedings Paperen_US
dspace.entity.typePublication

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