Real image dehazing based on model optimization and luminance enhancement - Li, Lingyu; Tao, Zhiyong; Lin, Sen (Scientific Bulletin. Series C, Electrical Engineering and Computer Science, 2025)
Addressing the issues of blurred details, color distortion, and reduced brightness in hazy images, we propose a dehazing method grounded in model optimization and brightness enhancement. Firstly, the traditional atmospheric scattering model is optimized based on the dark channel prior theory. Second, a luminance augmentation branch is proposed to improve the image brightness. Finally, the images processed by both the model optimization and luminance enhancement branches are fused and subsequently color-corrected to enhance the visual quality of the images. Experimental results on the RESIDE dataset and realworld images show that our method outperforms classical and the latest dehazing methods.