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基于色域分析的大雾图像特征提取与等级识别方法
引用本文:苗开超,罗希昌,张淑静,王飞,周建平.基于色域分析的大雾图像特征提取与等级识别方法[J].科学技术与工程,2019,19(35):228-233.
作者姓名:苗开超  罗希昌  张淑静  王飞  周建平
作者单位:安徽省公共气象服务中心,合肥230031;新疆塔城地区气象局,塔城834700
基金项目:国家自然科学基金(41575155)
摘    要:基于色域分析对大雾图像的特征展开研究,首先将大雾图像数值化,获取其RGB空间;其次将图像由RGB空间转换到YCbCr空间,提取其亮度特征;然后使用主成分分析法降维得到高层抽象特征,实现大雾图像特征提取;最后基于提取的特征空间,使用K近邻算法建立大雾识别模型,并对模型进行了测试。

关 键 词:色域分析  特征提取  图像识别  主成分分析  K近邻
收稿时间:2019/3/25 0:00:00
修稿时间:2019/8/21 0:00:00

Feature extraction and degree class of fog image based on chromatogram
Miao Kaichao,Luo Xichang,Zhang Shujing,and.Feature extraction and degree class of fog image based on chromatogram[J].Science Technology and Engineering,2019,19(35):228-233.
Authors:Miao Kaichao  Luo Xichang  Zhang Shujing  and
Institution:Anhui Public Meteorological Service Center,Anhui Public Meteorological Service Center,Anhui Public Meteorological Service Center,Anhui Public Meteorological Service Center,Anhui Public Meteorological Service Center
Abstract:based on gamut analysis, the characteristics of fog image are studied. Firstly, the RGB space of fog image is obtained by digitizing the image; secondly, the image is converted from RGB space to YCbCr space to extract its brightness characteristics; thirdly, the high-level abstract features are obtained by using principal component analysis (PCA) dimensionality reduction to realize feature extraction of fog image; finally, based on the extracted feature space, the K-nearest neighbor algorithm is used to build a larger image. The fog recognition model was tested.
Keywords:Color gamut  feature factor  image recognition  PCA  KNN
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