计算机工程与应用2019，Vol.55Issue(10)：179-185,7.DOI:10.3778/j.issn.1002-8331.1806-0408
改进多尺度卷积神经网络的单幅图像去雾方法
Single Image Dehazing by Using Improved Multi-Scale Convolutional Neural Network
摘要
Abstract
As the current reported dehazing method is easy to cause halo and color distortion in the sky region, a single image dehazing algorithm by combining multi-scale convolution with scattering model is proposed. Firstly, the original haze image is convoluted with three different scales of convolution kernels. After a series of characteristic learning, the rough transmission is obtained. Then the transmission map is refined by using the guided filter. Secondly, according to the haze image and rough transmission, the global atmospheric light is known. Finally, with the refined transmission map and the calculated atmospheric light, the final dehazed image is inversely derived from the atmospheric scattering model. Experimental results show that the proposed algorithm is more natural to deal with the sky area, and it has better restora-tion effect on image texture and color distortion.关键词
图像去雾/图像复原/多尺度卷积/散射模型Key words
image dehazing/image restoration/multi-scale convolution/scattering model分类
信息技术与安全科学引用本文复制引用
雎青青,李朝锋,桑庆兵..改进多尺度卷积神经网络的单幅图像去雾方法[J].计算机工程与应用,2019,55(10):179-185,7.基金项目
国家自然科学基金(No.61373116) （No.61373116）
陕西省科技统筹创新工程计划项目(No.2016KTZDGY04-01) （No.2016KTZDGY04-01）
陕西省工业领域一般项目(No.2018GY-013) （No.2018GY-013）
陕西省教育厅项目(No.18JK0697) （No.18JK0697）
西安市科技局科技计划项目(No.2017084CG/RC047 (XAYD001)) （No.2017084CG/RC047 (XAYD001）
咸阳市科技局项目(No.2017k01-25-3). （No.2017k01-25-3）
