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author:

Yuan, P. (Yuan, P..) [1] | Lin, L. (Lin, L..) [2] | Lin, J. (Lin, J..) [3] | Liao, Y. (Liao, Y..) [4] | Zhao, T. (Zhao, T..) [5]

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Scopus

Abstract:

Aerial imaging aims to produce well-exposed images with rich details. However, aerial photography may encounter low-light conditions during dusk or dawn, as well as on cloudy or foggy days. In such low-light scenarios, aerial images often suffer from issues such as underexposure, noise, and color distortion. Most existing low-light imaging methods struggle with achieving realistic exposure and retaining rich details. To address these issues, we propose an Aerial Low-light Imaging with Color-monochrome Engagement (ALICE), which employs a coarse-to-fine strategy to correct low-light aerial degradation. First, we introduce wavelet transform to design a perturbation corrector for coarse exposure recovery while preserving details. Second, inspired by the binocular low-light imaging mechanism of the human visual system, we introduce uniformly well-exposed monochrome images to guide a refinement restorer, processing luminance and chrominance branches separately for further improved reconstruction. Within this framework, we design a Reference-based Illumination Fusion Module (RIFM) and an Illumination Detail Transformation Module (IDTM) for targeted exposure and detail restoration. Third, we develop a Dual-camera Low-light Aerial Imaging (DuLAI) dataset to evaluate our proposed ALICE. Extensive qualitative and quantitative experiments demonstrate the effectiveness of our ALICE, achieving a PSNR improvement of at least 19.52% over 12 state-of-the-art methods on the DuLAI Syn-R1440 dataset, while providing more balanced exposure and richer details. Our codes and datasets will be made publicly available after the peer review process. © 1980-2012 IEEE.

Keyword:

Color-Monochrome Cameras Low-light Aerial Imaging

Community:

  • [ 1 ] [Yuan P.]Fuzhou University, Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fujian, Fuzhou, 350108, China
  • [ 2 ] [Lin L.]Fuzhou University, Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fujian, Fuzhou, 350108, China
  • [ 3 ] [Lin L.]Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou, 350108, China
  • [ 4 ] [Lin J.]Peking University, School of Electronic and Computer Engineering, Shenzhen Graduate School, Shenzhen, 518055, China
  • [ 5 ] [Liao Y.]Fuzhou University, Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fujian, Fuzhou, 350108, China
  • [ 6 ] [Zhao T.]Fuzhou University, Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fujian, Fuzhou, 350108, China
  • [ 7 ] [Zhao T.]Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou, 350108, China

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Source :

IEEE Transactions on Geoscience and Remote Sensing

ISSN: 0196-2892

Year: 2025

7 . 5 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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