Derivative feature and residual spatial attention for low-light image enhancement

研究成果: Conference contribution

抄録

Images taken in low-light conditions often have the problem of poor visibility. Besides inadequate lightings, different types of image quality degradation, such as a large amount of noise and color loss due to the limited quality of cameras and camera ISO setting, cause low quality of the captured image. However, directly amplifying the darkness of the lowlight image will inescapably bring into the pollution of the image. Therefore, the task of low-light image enhancement needs to kindle the dark regions and remove image degradation. To achieve this task, our work builds a Retinex theorybased neural network, which decomposes the input images into an illumination map and a reflectance map. Illumination map, representing the light information, is used for brightness adjustment, while reflectance map, representing the color information, is responsible for reconstructing low-light image into enhanced image with adjusted illumination map. However, there are few studies that notice the derivative of the image is used to solve the noise problem in Retinex decomposition and use spatial attention-based residual structures to increase the effect of light enhancement. For Decomposition sub-Network (Decom-Net), we purpose derivative features to alleviate the occurrence of noise in the reflectance map in the process of low-light image decomposition. For Illumination Enhancement sub-Network (Relight- Net), we use the Gaussian blur for reducing the problem of brightness enhancement degradation and build the Residual Spatial Attention Block (RSAB) to enlarge the volume and increase the capability of pixel-to-pixel mapping. Experiments are implemented to shows the effectiveness of our network, which improves the performance of previous methods on a large scale.

本文言語English
ホスト出版物のタイトルThirteenth International Conference on Signal Processing Systems, ICSPS 2021
編集者Qingli Li, Kezhi Mao, Yi Xie
出版社SPIE
ISBN(電子版)9781510653177
DOI
出版ステータスPublished - 2022
イベント13th International Conference on Signal Processing Systems, ICSPS 2021 - Shanghai, China
継続期間: 2021 11月 122021 11月 15

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
12171
ISSN(印刷版)0277-786X
ISSN(電子版)1996-756X

Conference

Conference13th International Conference on Signal Processing Systems, ICSPS 2021
国/地域China
CityShanghai
Period21/11/1221/11/15

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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