Dual Autoencoder Network for Retinex-Based Low-Light Image Enhancement

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 smooth illumination component which is brighter than an...

Celý popis

Podrobná bibliografia

Vydané v:	IEEE access Ročník 6; s. 22084 - 22093
Hlavní autori:	Park, Seonhee, Yu, Soohwan, Kim, Minseo, Park, Kwanwoo, Paik, Joonki
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.01.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Autoencoder Brightness Convolution Image edge detection Image enhancement image processing Image reconstruction Lighting neural networks Noise reduction unsupervised learning variational retinex model
ISSN:	2169-3536, 2169-3536
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!