基于特征融合的快速图像去雾方法

针对图像去雾问题, 提出一种基于特征融合的快速单幅图像去雾方法, 解决了暗通道方法存在的块效应问题. 该方法先采用基于K均值聚类的暗通道先验求得粗尺度下的透射率, 再通过分析雾对成像的影响, 提取有雾图像自身能反映景深变化的饱和度作为细尺度的透射率, 最后通过图像融合技术得到精确的透射率. 通过对
各种真实有雾场景进行测试的实验结果表明, 该方法简单且有效, 能得到理想的去雾效果.

Fast Image Dehazing Method Based on Feature Fusion

Aiming at the problem of image processing, we proposeda fast single image dehazing method based on feature fusion, and solved the problem of the block effect of dark channel method. By means of the dark channel prior based on K-means clustering, the coarse scale transmission was obtained. By analyzing the effect of haze on imaging, we extracted the saturation of hazy image itself as fine scale transmission, which could reflect the change of scene depth effectively. Finally, we obtained accurate transmission via image fusion technique. Through the test of a variety of real scene images, the experiment results show that the method is simple and effective, and can get ideal dehazing result.