Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Seonhee Park"'
Publikováno v:
IEEE Access, Vol 6, Pp 22084-22093 (2018)
This paper presents a dual autoencoder network model based on the retinex theory to perform the low-light enhancement and noise reduction by combining the stacked and convolutional autoencoders. The proposed method first estimates the spatially smoot
Externí odkaz:
https://doaj.org/article/c750038f87484acd8db10496eb311503
Publikováno v:
EURASIP Journal on Image and Video Processing, Vol 2017, Iss 1, Pp 1-11 (2017)
Abstract This paper presents a low-light image restoration method based on the variational Retinex model using the bright channel prior (BCP) and total-variation minimization. The proposed method first estimates the bright channel to control the amou
Externí odkaz:
https://doaj.org/article/639fb5a81521479d930b26dacd021cc3
Publikováno v:
Applied Sciences, Vol 8, Iss 8, p 1321 (2018)
This paper presents a computationally efficient haze removal and image enhancement methods. The major contribution of the proposed research is two-fold: (i) an accurate atmospheric light estimation using principal component analysis, and (ii) learnin
Externí odkaz:
https://doaj.org/article/7cf47da3b67745ecae1f230a08706cbf
Autor:
Seonhee Park, Yi Sangbong
Publikováno v:
Korean Technology Education Association. 20:69-87
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::edb0b29647c979adfe3d22743b5b023e
https://doi.org/10.34138/kjte.2020.20.1.69
https://doi.org/10.34138/kjte.2020.20.1.69
Publikováno v:
IEIE Transactions on Smart Processing & Computing. 7:36-48
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d28713ac58b1456a96287f1f7da587fc
https://doi.org/10.5573/ieiespc.2018.7.1.036
https://doi.org/10.5573/ieiespc.2018.7.1.036
Publikováno v:
IEEE Transactions on Consumer Electronics. 64:69-76
This paper presents a neural network-based method to generate multiple images with different exposures from a single input low dynamic range (LDR) image for improved high dynamic range (HDR) imaging. The proposed algorithm consists of three steps: 1)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::febbadfc205b2632821a384cc81b2ed9
https://doi.org/10.1109/tce.2018.2811257
https://doi.org/10.1109/tce.2018.2811257
Publikováno v:
IEEE Access, Vol 6, Pp 22084-22093 (2018)
This paper presents a dual autoencoder network model based on the retinex theory to perform the low-light enhancement and noise reduction by combining the stacked and convolutional autoencoders. The proposed method first estimates the spatially smoot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fbad9e2a6efecdec78e714a7200da04f
https://ieeexplore.ieee.org/document/8307190/
https://ieeexplore.ieee.org/document/8307190/
Autor:
Jinyoung Hwang, Seonhee Park
Publikováno v:
The Journal of Korean Public Policy. 19:41-68
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a5ae9ca5a54ae7930b60a8581034389
https://doi.org/10.37103/kapp.19.4.3
https://doi.org/10.37103/kapp.19.4.3
Publikováno v:
Signal Processing: Image Communication. 58:99-110
This paper presents a novel variational framework for low-light image enhancement. The proposed enhancement algorithm simultaneously performs brightness enhancement and noise reduction using a variational optimization. An edge-preserved noise reducti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33a67439a551f23fcd3412ed3c222bba
https://doi.org/10.1016/j.image.2017.06.016
https://doi.org/10.1016/j.image.2017.06.016
Publikováno v:
Journal of Special Education. 24:167-187
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::622407a84d347f8535d1150c146687f7
https://doi.org/10.34249/jse.2017.24.1.167
https://doi.org/10.34249/jse.2017.24.1.167