基于图像分块与特征融合的户外图像天气识别  

Outdoor Image Weather Recognition Based on Image Blocks and Feature Fusion

作　　者：左杰格 柳晓鸣[1] 蔡兵 ZUO Jie-ge;LIU Xiao-ming;CAI Bing(School of Information Science and Technology,Dalian Maritime University,Dalian,Liaoning 116026,China)

机构地区：[1]大连海事大学信息科学技术学院,辽宁大连116026

出　　处：《计算机科学》2022年第3期197-203,共7页Computer Science

基　　金：国家自然科学基金(62001078);福建海事局基金(2018Z0093)。

摘　　要：在视频监控及智能交通等领域,雾、雨、雪等恶劣天气会严重影响视频图像能见度,因此快速识别出当前的天气情况,并自适应地对监控视频进行清晰化处理极为重要。针对传统天气识别方法效果差以及天气图像数据集缺乏的问题,构建了一个多类别天气图像分块数据集,并提出了一种基于图像分块与特征融合的天气识别算法。该算法基于传统方法提取平均梯度、对比度、饱和度、暗通道4种特征作为天气图像的浅层特征,基于迁移学习对VGG16预训练模型进行微调,提取微调模型的全连接层特征作为天气图像的深层特征,将天气图像浅层特征与深层特征融合作为最终特征用于训练Softmax分类器,实现对雾、雨、雪、晴4类天气图像的识别。实验结果表明,所提算法能达到99.26%的识别准确率,并且可作为天气识别模块应用于自适应视频图像清晰化处理系统。In video surveillance and intelligent traffic,bad weather such as foggy,rainy and snowy can seriously affect the visibility of video images.Therefore,it is very important to quickly identify the current weather conditions and make adaptive clearness processing of surveillance videos.Aiming at the problems of poor effect of traditional weather recognition methods and lack of weather image data sets,a multi-class weather image blocks data set is constructed,and a weather recognition algorithm based on image blocks and feature fusion is proposed.The algorithm uses traditional methods to extract four features,namely average gradient,contrast,saturation and dark channel,which are taken as the shallow features of weather images.The algorithm uses transfer learning to fine-tune the VGG16pre-training model,and extracts the full-connection layer features of the fine-tuning model,which are taken as the deep features of the weather image.The shallow and deep features of weather images are fused and used as the final features to train the Softmax classifier.The classifier can realize the recognition of foggy,rainy,snowy and sunny weather images.Experimental results show that the recognition accuracy of the proposed algorithm can reach 99.26%,and the algorithm can be used as a weather recognition module in the adaptive video image sharpening system.

关 键 词：图像分块 天气识别 卷积神经网络 迁移学习 特征提取 特征融合 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]