424 0

Full metadata record

DC FieldValueLanguage
dc.contributor.author문영식-
dc.date.accessioned2020-01-13T05:13:34Z-
dc.date.available2020-01-13T05:13:34Z-
dc.date.issued2019-02-
dc.identifier.citationAdvances in Science, Technology and Engineering Systems, v. 4, No. 1, Page. 159-164en_US
dc.identifier.issn2415-6698-
dc.identifier.urihttps://astesj.com/v04/i01/p15/-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/121721-
dc.description.abstractLow contrast images degrade the performance of image processing system. To solve the issue, plenty of image enhancement methods have been proposed. But the methods work properly on the fixed environment or specific images. The methods dependent on fixed image conditions cannot perform image enhancement properly and perspective of smart device users, algorithms including iterative calculations are inconvenient for users. To avoid these issues, we propose a locally adaptive contrast enhancement method using CNN and simple reflection model. The experimental results show that the proposed method reduces over-enhancement, while recovering the details of the low contrast regions.en_US
dc.language.isoen_USen_US
dc.publisherASTES Publishersen_US
dc.subjectImage Enhancementen_US
dc.subjectConvolutional Neural Networken_US
dc.subjectReflection Modelen_US
dc.subjectMachine Learningen_US
dc.titleLow contrast image enhancement using convolutional neural network with simple reflection modelen_US
dc.typeArticleen_US
dc.relation.no1-
dc.relation.volume4-
dc.identifier.doi10.25046/aj040115-
dc.relation.page159-164-
dc.relation.journalAdvances in Science, Technology and Engineering Systems-
dc.contributor.googleauthorMoon, Young Shik-
dc.contributor.googleauthorHan, Bok Gyu-
dc.contributor.googleauthorYang, Hyeon Seok-
dc.contributor.googleauthorLee, Ho Gyeong-
dc.relation.code2020000716-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF COMPUTING[E]-
dc.sector.departmentDIVISION OF COMPUTER SCIENCE-
dc.identifier.pidysmoon-
Appears in Collections:
COLLEGE OF COMPUTING[E](소프트웨어융합대학) > COMPUTER SCIENCE(소프트웨어학부) > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE