Low-Illumination-Based Enhancement Algorithm of Color Images with Fog

To solve the problem of uneven illumination and color distortion in the Retinex algorithm for defogging, we propose an enhancement algorithm of color images with fog based on low illumination. First, this algorithm converts the red-green-blue (RGB) image into the hue-saturation-value (HSV) spatial region, extracts the value (V) component, and performs Gamma correction for the V component after the single-scale Retinex algorithm is applied to the V component. Then, the Gaussian filter in the MSRCR algorithm is changed into guided filtering and the low-pass filtering is performed. Finally, the images obtained by the improved SSR algorithm, the MSRCR algorithm, and the Retinex algorithm based on the Laplace pyramid arc weighted and fused. The proposed algorithm can get a good effect in fog removal and can effectively suppress halo and improve color distortion. As for those images processed by the proposed algorithm, the image similarity, information entropy and other indicators have ken improved.