Dataset Open Access
RELLISUR: A Real Low-Light Image Super-Resolution Dataset
Andreas Aakerberg; Kamal Nasrollahi; Thomas B. Moeslund
The RELLISUR dataset contains real low-light low-resolution images paired with normal-light high-resolution reference image counterparts. This dataset aims to fill the gap between low-light image enhancement and low-resolution image enhancement (Super-Resolution (SR)) which is currently only being addressed separately in the literature, even though the visibility of real-world images is often limited by both low-light and low-resolution. The dataset contains 12750 paired images of different resolutions and degrees of low-light illumination, to facilitate learning of deep-learning based models that can perform a direct mapping from degraded images with low visibility to high-quality detail rich images of high resolution.
| Name | Size | |
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RELLISUR.zip
md5:f3b94e144ffd6ec906cf568c5e7ec00b |
8.9 GB | Download |
| All versions | This version | |
|---|---|---|
| Views | 360 | 360 |
| Downloads | 525 | 525 |
| Data volume | 4.6 TB | 4.6 TB |
| Unique views | 323 | 323 |
| Unique downloads | 206 | 206 |
- Publication date:
- August 23, 2021
- DOI:
-
- Keyword(s):
- Super-resolution Low-light enhancement image processing
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International