Improved Dark Channel Prior for Image Defogging

Fan Yang, Yunjie Hu
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Abstract

An image defogging algorithm with improved transmittance is proposed for the problem of residual fog in the defogged image obtained by the dark channel a prior algorithm. In this paper, the atmospheric light value in the scene is estimated using the quadrature method, and the minimum map in the dark channel algorithm is further optimized using the super pixel segmentation algorithm with median filtering and combined at the pixel level. The obtained transmittance map is then filtered with a guide to eliminate texture effects. Finally, the defogged image is transferred to the HSI (Hue-Saturation-Intensity) color space for image enhancement. The results of the experiment showed that compared with the classical dark channel algorithm, the algorithm in this paper has obvious defogging effect, complete image information retention, and lower algorithm complexity.
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改进暗通道先验图像去雾
针对暗通道先验算法得到的去雾图像中存在残雾问题,提出了一种提高透光率的图像去雾算法。本文利用正交法估计场景中的大气光值,利用中值滤波的超像素分割算法进一步优化暗通道算法中的最小映射,并在像素级进行组合。得到的透光率图然后用导流器过滤以消除纹理效果。最后,将去雾图像传输到HSI(色调-饱和度-强度)色彩空间进行图像增强。实验结果表明,与经典暗通道算法相比,本文算法除雾效果明显,图像信息保留完整,算法复杂度较低。
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