光子学报, 2010, 39 (6): 1026, 网络出版: 2010-08-31   

基于偏振光谱BRDF图像的物质分类

Materials Classification Based on Spectropolarimetric BRDF Imagery
作者单位
西北工业大学自动化学院,西安 710072
摘要
提出一种基于偏振光谱二向反射分布函数图像的物质自动分类方法,该方法主要选择偏振光谱二向反射分布函数信息作为新的特征用于物质自动分类.采用支撑向量机的分类方法对不同的天气条件(晴天、多云、阴天)下处于杂乱的自然草地背景环境中的典型目标进行分类,最后比较三种不同特征选择对于分类准确度的影响.采取三种不同的特征选取方法,分别为采用单一的光谱特征、偏振光谱特征及偏振光谱二向反射分布函数特征.最后通过实验得出:将偏振光谱二向反射分布函数作为分类特征在三种不同的天气情况下,分类准确度都较高,特别是在阴天天气条件下,分类准确度明显高于其它两种特征选择.即使是在阴天低照度下的场景中,当不同目标和背景之间的灰度很接近时,采用本文方法也能准确的进行自动分类.
Abstract
A new classify method based on spectropolarimetric BRDF imagery is proposed.The performances of three different selected features in classifyication results under various weather conditions including sunny sky,cloudy,and dark sky are emphasized.The three selected features are material spectral information,spectropolarimetric information,and spectropolarimetric BRDF information respectively.Support Vector Machine method is used to classify targets in clutter grass environments,then the classify results based on spectropolarimetric BRDF features are compared with the other two features under the three different weather conditions respectively.The results show that the method based on spectropolarimetric BRDF features performs the best among the three,no matter what the weather conditions are,and its advantage shows most evidently especially in the dark sky.Selecting the spectropolarimetric BRDF information as features in the materials classification will enhance the precision at most time,even in the case when the gray values between backgrounds and targets are very near.

陈超, 赵永强, 程咏梅, 潘泉, 罗丽. 基于偏振光谱BRDF图像的物质分类[J]. 光子学报, 2010, 39(6): 1026. CHEN Chao, ZHAO Yong-qiang, CHENG Yong-mei, PAN Quan, LUO Li. Materials Classification Based on Spectropolarimetric BRDF Imagery[J]. ACTA PHOTONICA SINICA, 2010, 39(6): 1026.

本文已被 3 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!