Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/95934
Title: | Lightening network for low-light image enhancement | Authors: | Wang, L Liu, Z Siu, W Lun, DPK |
Issue Date: | 2020 | Source: | IEEE transactions on image processing, 2020, v. 29, p. 7984-7996 | Abstract: | Low-light image enhancement is a challenging task that has attracted considerable attention. Pictures taken in low-light conditions often have bad visual quality. To address the problem, we regard the low-light enhancement as a residual learning problem that is to estimate the residual between low- and normal-light images. In this paper, we propose a novel Deep Lightening Network (DLN) that benefits from the recent development of Convolutional Neural Networks (CNNs). The proposed DLN consists of several Lightening Back-Projection (LBP) blocks. The LBPs perform lightening and darkening processes iteratively to learn the residual for normal-light estimations. To effectively utilize the local and global features, we also propose a Feature Aggregation (FA) block that adaptively fuses the results of different LBPs. We evaluate the proposed method on different datasets. Numerical results show that our proposed DLN approach outperforms other methods under both objective and subjective metrics. | Keywords: | Low-light image enhancement Image processing Deep learning |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE transactions on image processing | ISSN: | 1057-7149 | EISSN: | 1941-0042 | DOI: | 10.1109/TIP.2020.3008396 | Rights: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication L. Wang, Z. Liu, W. Siu and D. P. K. Lun, "Lightening Network for Low-Light Image Enhancement," in IEEE Transactions on Image Processing, vol. 29, pp. 7984-7996, 2020 is available at https://dx.doi.org/10.1109/TIP.2020.3008396. |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
EIE-0186_Wang_Lightening_Network_Low-Light.pdf | Pre-Published version | 2.07 MB | Adobe PDF | View/Open |
Page views
64
Last Week
0
0
Last month
Citations as of May 19, 2024
Downloads
161
Citations as of May 19, 2024
SCOPUSTM
Citations
160
Citations as of May 17, 2024
WEB OF SCIENCETM
Citations
128
Citations as of May 16, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.