基于对比度增强与非均匀大气散射模型的图像去雾OA

To overcome the limitations of the dark channel prior dehazing algorithm,such as color distortion and Halo artifacts,this study proposes an image dehazing method based on contrast enhancement and a non-uniform atmospheric scattering model.First,the hazy image undergoes adaptive histogram equalization with color preservation to enhance contrast and color saturation.Second,considering the non-uniform distribution of atmospheric light,a non-uniform atmospheric light estimation strategy is introduced.A coarse estimation is initially obtained and subsequently refined using a guided filter.The transmission map is further optimized using a weighted least squares filter to suppress block artifacts while preserving image details.Finally,the dehazed image is reconstructed using the non-uniform atmospheric scattering model.Both qualitative and quantitative experimental results show that the algorithm effectively removes haze,producing images with natural color representation and clear,detailed textures,outperforming existing methods.