Improved Image Dehazing Algorithm Based on Haze-line and Dark Channel Prior

To address the problem of image dehazing distortion caused by inaccurate estimation of atmospheric light value and transmission in existing image dehazing algorithms, an improved image dehazing algorithm based on dark channel prior and haze-line prior is proposed. First, we compute the global relative haze concentration of the image using the relationship between haze concentration and the difference in brightness and saturation in HSV space and combine the high-pixel value corresponding to the dark channel map to set the weight coefficient that can automatically select the appropriate atmospheric light value. Second, we use the rough transmittance value obtained by the dark channel prior to correct the maximum radius transmittance in each haze-line, and then introduce a tolerance parameter to optimize the transmittance of bright pixels. Next, fast guiding filtering is introduced to further optimize the transmittance maps. Finally, the final haze-free image based on the atmospheric scattering model is obtained. The experimental results show that the image dehazing algorithm proposed in this research outperforms the current algorithms in terms of subjective visual effect and objective data.

Automated summary

An improved image dehazing algorithm based on dark channel prior and haze-line prior is proposed in this research to address the issue of image dehazing distortion caused by inaccurate estimation of atmospheric light value and transmission in existing algorithms. Experimental results demonstrate that the proposed algorithm surpasses current algorithms in terms of subjective visual effect and objective data.