Enhance dim images better and simpler using imperfectly aligned images with CIDN
Enhance dim images better and simpler using imperfectly aligned images with CIDN
Enhancing Low-Light Images in Real World via Cross-Image Disentanglement
arXiv paper abstract https://arxiv.org/abs/2201.03145v1
arXiv PDF paper https://arxiv.org/pdf/2201.03145v1.pdf
Images captured in the low-light ... suffer from low visibility and ... artifacts, e.g., real noise.
Existing supervised enlightening algorithms require a large set of pixel-aligned training image pairs, which are hard to prepare
... instead of using perfectly aligned images for training, ... creatively employ the misaligned real-world images as the guidance
... propose a Cross-Image Disentanglement Network (CIDN) to separately extract cross-image brightness and image-specific content features from low/normal-light images.
... CIDN can simultaneously correct the brightness and suppress image artifacts in the feature domain, which largely increases the robustness to the pixel shifts.
... model achieves state-of-the-art performances on both the newly proposed dataset and other popular low-light datasets.
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