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Real-time video enhancement for various weather conditions using dark channel and fuzzy logic

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dc.Conferencecode112912
dc.Conferencedate3 June 2014 through 5 June 2014
dc.Conferencename2014 International Conference on Computer and Information Sciences, ICCOINS 2014
dc.citedby3
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.authorAlajarmeh A.en_US
dc.contributor.authorSalam R.A.en_US
dc.contributor.authorMarhusin M.F.en_US
dc.contributor.authorKhairi Abdul Rahimen_US
dc.date.accessioned2024-05-29T01:58:00Z
dc.date.available2024-05-29T01:58:00Z
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. � 2014 IEEE.
dc.description.natureFinalen_US
dc.identifier.ArtNo6868351
dc.identifier.doi10.1109/ICCOINS.2014.6868351
dc.identifier.isbn9781480000000
dc.identifier.scopus2-s2.0-84938793154
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84938793154&doi=10.1109%2fICCOINS.2014.6868351&partnerID=40&md5=1a195156e08b72243bb1b3821be04047
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/9970
dc.languageEnglish
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings
dc.sourceScopus
dc.subjectAirlighten_US
dc.subjectDark channelen_US
dc.subjectFuzzy logicen_US
dc.subjectReal-time applicationsen_US
dc.subjectAutomobile driversen_US
dc.subjectBalloonsen_US
dc.subjectInformation scienceen_US
dc.subjectMembership functionsen_US
dc.subjectRainen_US
dc.subjectVisibilityen_US
dc.subjectAirlighten_US
dc.subjectAtmospheric scattering modelsen_US
dc.subjectDark channelen_US
dc.subjectDegree of reliabilityen_US
dc.subjectDriver assistance systemen_US
dc.subjectFuzzy membership functionen_US
dc.subjectReal-time applicationen_US
dc.subjectStatistical regularityen_US
dc.subjectFuzzy logicen_US
dc.titleReal-time video enhancement for various weather conditions using dark channel and fuzzy logicen_US
dc.typeArticleen_US
dspace.entity.typePublication

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