DEN: Disentanglement and Enhancement Networks for Low Illumination Images

Nelson Chong Ngee Bow, Vu Hoang Tran, Punchok Kerdsiri, Yuen Peng Loh, Ching-Chun Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Though learning-based low-light enhancement methods have achieved significant success, existing methods are still sensitive to noise and unnatural appearance. The problems may come from the lack of structural awareness and the confusion between noise and texture. Thus, we present a lowlight image enhancement method that consists of an image disentanglement network and an illumination boosting network. The disentanglement network is first used to decompose the input image into image details and image illumination. The extracted illumination part then goes through a multi-branch enhancement network designed to improve the dynamic range of the image. The multi-branch network extracts multi-level image features and enhances them via numerous subnets. These enhanced features are then fused to generate the enhanced illumination part. Finally, the denoised image details and the enhanced illumination are entangled to produce the normallight image. Experimental results show that our method can produce visually pleasing images in many public datasets.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages419-422
Number of pages4
ISBN (Electronic)9781728180670
DOIs
StatePublished - 1 Dec 2020
Event2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020 - Virtual, Macau, China
Duration: 1 Dec 20204 Dec 2020

Publication series

Name2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020

Conference

Conference2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020
Country/TerritoryChina
CityVirtual, Macau
Period1/12/204/12/20

Keywords

  • image disentanglement
  • low-light enhancement
  • multi-branch enhancement network

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