基于自适应流形滤波的高光谱图像分类方法  

Hyperspectral Image Classification Method Based on Adaptive Manifold Filtering

作　　者：廖建尚[1] 王立国[2] 郝思媛[3] Liao Jianshang;Wang Liguo;Hao Siyuan(School of Rail Transit, Guangdong Communication Polytechnic, Guangzh,ou, Guangdong 510650, China;College of Information and Communication Engineering, Harbin Engineering University, Harbin, Heilongjiang 150001, China;School of Communication and Electronic Engineering, Qingdao University of Technology, Qingdao, Shandong 266520, Chin)

机构地区：[1]广东交通职业技术学院轨道交通学院,广东广州510650 [2]哈尔滨工程大学信息与通信工程学院,黑龙江哈尔滨150001 [3]青岛理工大学通信与电子工程学院,山东青岛266520

出　　处：《激光与光电子学进展》2018年第4期151-161,共11页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(61275010;61675051);广东省科技计划项目(2017ZC0358);广州市科技计划项目(201804010262);广东交通职业技术学院重点科研项目(2017-1-001)

摘　　要：滤波器在提取高光谱图像空间纹理信息时往往容易陷入局部的特征提取。针对这一问题,提出一种自适应流形滤波的高光谱图像分类算法(AMF-SVM)。该方法采用自适应寻优,先计算第一个流形,然后根据流形树高度进行递归投射、平滑和聚合处理,结合处理结果对高光谱进行线性滤波,得到较好的空间特征,并由支持向量机(SVM)完成分类,最后获得最优的分类结果。实验表明,相比使用光谱信息、高光谱降维、空谱信息结合的SVM分类方法,边缘保持滤波以及递归滤波的方法,AMF-SVM对高光谱图像的分类精度有较大提高,充分说明了该方法的有效性。Spatial texture information extraction of hyperspectral image by filter often falls into local texture extraction. According to the problem, an algorithm of hyperspectral image classification based on adaptive manifold filtering （AMF-SVM） is proposed. This method uses adaptive optimization. The first manifold is calculated. Then, hyperspectral image with manifold is recursively splatted, blurred, and sliced according to the height of the manifold tree. Combined with the handling results, hyperspectral image is applicated to the linear filtering, the results are classified by support vector machine （SVM）, and then the optimal classification is obtained. Experimental results show that the AMF-SVM algorithm is better than original SVM classification methods using the spectrum information, dimensionality reduction, and the spatial-spectral information, and the methods of edge-preserving filtering and recursive filtering. Performance of the classification for hyperspectral image with AMF-SVM is greatly improved, and effectiveness of this method is fully verified.

关 键 词：图像处理 高光谱图像 自适应流形滤波 空间纹理信息 全局寻优 分类 

分 类 号：TP753[自动化与计算机技术—检测技术与自动化装置]