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dc.contributor.author문영식-
dc.date.accessioned2019-05-22T01:05:28Z-
dc.date.available2019-05-22T01:05:28Z-
dc.date.issued2018-01-
dc.identifier.citation2018 IEEE International Conference on Consumer Electronics (ICCE), Page. 501-502en_US
dc.identifier.issn2158-4001-
dc.identifier.urihttps://ieeexplore.ieee.org/document/8326096-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/105322-
dc.description.abstractLow contrast images obtained from smart phones or any imaging devices are difficult to process by image processing systems and general users. Therefore, an enhancement of low contrast image is an important task in image processing and for device users. In this paper, we propose a method to detect low contrast regions using CNN(Convolutional Neural Network) and to improve the image quality by using chromatic contrast weight. Experiments show that the proposed method reduces over enhancement, while recovering details of low contrast regions.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.titleLocally Adaptive Contrast Enhancement Using Convolutional Neural Networken_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICCE.2018.8326096-
dc.relation.page501-502-
dc.contributor.googleauthorHan, Bok Gyu-
dc.contributor.googleauthorYang, Hyeon Seok-
dc.contributor.googleauthorMoon, Young Shik-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF COMPUTING[E]-
dc.sector.departmentDIVISION OF COMPUTER SCIENCE-
dc.identifier.pidysmoon-
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COLLEGE OF COMPUTING[E](소프트웨어융합대학) > COMPUTER SCIENCE(소프트웨어학부) > Articles
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