基于Pyramid-Kuwahara滤波器的航拍图像去雾方法OA北大核心CSTPCD

Aiming to address the challenges of the current UAV aerial image de-fogging method,including difficulties in considering de-fogging for different depths of field,excessive loss of edge details,and ineffective results,this paper proposes a de-fogging method based on the Pyramid-Kuwahara filter.Firstly,atmospheric light estimation and transmittance are solved using an improved dark channel prior method.Secondly,a multi-scale filter called Pyramid-Kuwahara is designed to optimize and extract atmospheric light details.Then,a method named MFRTV is proposed to enhance detail information in transmission based on the designed filter.Finally,the restored fog-free image is obtained by utilizing the atmospheric scattering model along with optimized transmittance and atmospheric light maps generated by the algorithm.Experimental results demonstrate that our proposed fog removal algorithm effectively restores image details in different depths of field while significantly reducing fog presence in experimental images.Moreover,it successfully removes fog even at further depths of field achieving in enhanced subjective visual effects and increased information richness compared to other control algorithms.The proposed algorithm exhibits significant improvements in parameters such as entropy,FADE(fog area density estimation),structural similarity index(SSIM),and average gradient.