Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method

Nanjing University · Australian National University · +3 more institutions

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Abstract

As the quality of optical sensors improves, there is a need for processing large-scale images. In particular, the ability of devices to capture ultra-high definition (UHD) images and video places new demands on the image processing pipeline. In this paper, we consider the task of low-light image enhancement (LLIE) and introduce a large-scale database consisting of images at 4K and 8K resolution. We conduct systematic benchmarking studies and provide a comparison of current LLIE algorithms. As a second contribution, we introduce LLFormer, a transformer-based low-light enhancement method. The core components of LLFormer are the axis-based multi-head self-attention and cross-layer attention fusion block, which…

Citation impact

415
total citations
FWCI
24.44
Percentile
100%
References
44
Citations per year

Authors

6

Topics & keywords

Keywords
  • Computer science
  • Benchmarking
  • Benchmark (surveying)
  • Artificial intelligence
  • Transformer
  • Pipeline (software)
  • Block (permutation group theory)
  • Computer vision
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