Image Enhancement Method Based on Dark Channel Prior

According to the characteristics of foggy images, such as high noise, low resolution and uneven illumination, an improved foggy image enhancement method based on dark channel priority is proposed, which solves the problems of that the color of large area is uneven and the overall color of the image is dark when the traditional dark channel prior method is used to remove fog. Firstly, the new algorithm refines the transmittance and optimizes the atmospheric light value, and converts the restored image to HSV space. Secondly, the brightness V component is enhanced by MSRCR algorithm improved by bilateral filtering, and the saturation S is improved by adaptive stretching algorithm. Finally, the image is converted from HSV space to RGB space to complete image enhancement. The experimental results show that from subjective evaluation and quantitative analysis the new algorithm overcomes the shortcomings of noise amplification and edge blur when the conventional enhancement algorithm enhances the image. It can improve image darkening and avoid image distortion. It has a good effect on preserving the edge information and has good adaptability and stability for fog image enhancement.