Low-Light Image Enhancement Method based on Multiscale Feature Fusion

To effectively solve the problems of insufficient brightness, poor contrast, and high noise in low-light environments, this paper proposes a low-light image enhancement method based on multiscale feature fusion. The multilevel features of images are extracted by convolution kernels of different scales, and these multiscale features are fused organically by a feature fusion module. Finally, combining the processing technology of light enhancement and noise suppression, the visual effect of low-light image is significantly improved. The experimental results show that the proposed method has excellent performance in improving image brightness, contrast, and detail information, can effectively suppress noise, and has good adaptability and robustness.