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author:

Yuan, Pengwu (Yuan, Pengwu.) [1] | Lin, Liqun (Lin, Liqun.) [2] | Lin, Junhong (Lin, Junhong.) [3] | Liao, Yipeng (Liao, Yipeng.) [4] | Zhao, Tiesong (Zhao, Tiesong.) [5]

Indexed by:

EI

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 (HVS), 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. © 1980-2012 IEEE.

Keyword:

Aerial photography Color photography Energy efficiency Exposure controls Medical imaging Restoration Wavelet transforms

Community:

  • [ 1 ] [Yuan, Pengwu]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, Liqun]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, Junhong]Peking University, School of Electronic and Computer Engineering, Shenzhen Graduate School, Shenzhen; 518055, China
  • [ 4 ] [Liao, Yipeng]Fuzhou University, Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fujian, Fuzhou; 350108, China
  • [ 5 ] [Zhao, Tiesong]Fuzhou University, Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information, College of Physics and Information Engineering, Fujian, Fuzhou; 350108, China

Reprint 's Address:

  • [lin, liqun]fuzhou university, fujian key laboratory for intelligent processing and wireless transmission of media information, college of physics and information engineering, fujian, fuzhou; 350108, china

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Source :

IEEE Transactions on Geoscience and Remote Sensing

ISSN: 0196-2892

Year: 2025

Volume: 63

7 . 5 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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