Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method
Nanjing University · Australian National University · +3 more institutions
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
- FWCI
- 24.44
- Percentile
- 100%
- References
- 44
Authors
6Topics & keywords
- Computer science
- Benchmarking
- Benchmark (surveying)
- Artificial intelligence
- Transformer
- Pipeline (software)
- Block (permutation group theory)
- Computer vision