419 0

Low contrast image enhancement using convolutional neural network with simple reflection model

Title
Low contrast image enhancement using convolutional neural network with simple reflection model
Author
문영식
Keywords
Image Enhancement; Convolutional Neural Network; Reflection Model; Machine Learning
Issue Date
2019-02
Publisher
ASTES Publishers
Citation
Advances in Science, Technology and Engineering Systems, v. 4, No. 1, Page. 159-164
Abstract
Low 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.
URI
https://astesj.com/v04/i01/p15/https://repository.hanyang.ac.kr/handle/20.500.11754/121721
ISSN
2415-6698
DOI
10.25046/aj040115
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