Weak-Light Image Enhancement Method Based on Adaptive Local Gamma Transform and Color Compensation

In weak-light environments, images suffer from low contrast and the loss of details. Traditional image enhancement models are usually failure to avoid issue overenhancement. this paper, a simple novel correction method is proposed based on an adaptive local gamma transformation color compensation, which inspired by illumination reflection model. Our converts source into YUV space, Y component estimated with fast guided filter. The transform function used improve brightness adaptively adjusting parameters. Finally, dynamic range optimized compensation mechanism linear stretching strategy. By comparing state-of-the-art algorithms, it demonstrated that reduces influence uneven overenhancement visual effect low-light images.