测试科学与仪器2021，Vol.12Issue(4)：423-432,10.DOI:10.3969/j.issn.1674-8042.2021.04.006
基于HSI颜色空间的深度学习单幅图像去雾方法
Deeplearning method for single image dehazing based on HSI colour space
摘要
Abstract
The traditional single image dehazing algorithm is susceptible to the prior knowledge of hazy image and colour distortion.A new method of deep learning multi-scale convolution neural network based on HSI colour space for single image dehazing is proposed in this paper,which directly learns the mapping relationship between hazy image and corresponding clear image in colour,saturation and brightness by the designed structure of deep learning network to achieve haze removal.Firstly, the hazy image is transformed from RGB colour space to HSI colour space.Secondly,an end-to-end multi-scale full convolution neural network model is designed.The multi-scale extraction is realized by three different dehazing sub-networks:hue H, saturation S and intensity I,and the mapping relationship between hazy image and clear image is obtained by deep learning. Finally,the model was trained and tested with hazy data set.The experimental results show that this method can achieve good dehazing effect for both synthetic hazy images and real hazy images,and is superior to other contrast algorithms in subjective and objective evaluations.关键词
图像处理/图像去雾/HIS颜色空间/多尺度卷积神经网络Key words
image processing/image dehazing/HSI colour space/multi-scale convolution neural network引用本文复制引用
陈永,陶美风,郭红光..基于HSI颜色空间的深度学习单幅图像去雾方法[J].测试科学与仪器,2021,12(4):423-432,10.基金项目
National Natural Science Foundation of China(No.61963023) （No.61963023）
MOE(Ministry of Education in China)Project of Humanities and Social Sciences(No.19YJC760012) （Ministry of Education in China）
