利用大气散射模型的图像去雾研究

o obtain clear defogging images, a single image dehazing algorithm based on dark channel priori and boundary constraints is proposed. Firstly, for sky region and non-sky region, dark channel prior theory and boundary constraint theory are used to obtain transmission map respectively. Then, guided filtering is used to optimize the transmission map. Later, the improved tolerance mechanism is used to amplify the transmission in the sky region. Next, the precise atmospheric light value is obtained by combining the light channel prior theory and the dark channel prior theory. Finally, for the sky region and non-sky region, image fusion and histogram equalization are used to enhance the image brightness respectively. In this paper, the experimental results are analyzed from three indexes: peak signal to noise ratio(PSNR), mean squared error(MSE) and structural similarity(SSIM). Indicator data show that the dehazing image by our method has less distortion and higher clarity.