Low-illumination and noisy bridge crack image restoration by deep CNN denoiser and normalized flow module.

When applying deep learning and image processing techniques for bridge crack detection, the obtained images in real-world scenarios have severe image degradation problem. This study focuses on restoring low-illumination bridge crack images corrupted by noise to improve the accuracy of subsequent crack detection and semantic segmentation. The proposed algorithm consists of a deep CNN denoiser and a normalized flow-based brightness enhancement module.