D-SS Frame:deep spectral-spatial feature extraction and fusion for classification of panchromatic and multispectral images

作     者：Teffahi Hanane Yao Hongxun 

作者机构：School of Computer Science and TechnologyHarbin Institute of TechnologyHarbin 150001P.R.China Algerian Space AgencyAlgiers 16342Algeria 

出 版 物：《High Technology Letters》 (高技术通讯（英文版）)

年 卷 期：2018年第24卷第4期

页      面：378-386页

核心收录：

学科分类：07[理学] 08[工学] 

基　　金：Supported by the National Natural Science Foundation of China(No.61472103 61772158 U.1711265) 

主　　题：image classification feature extraction(FE) feature fusion sparse autoencoder stacked sparse autoencoder support vector machine(SVM) multispectral(MS)image panchromatic(PAN)image 

摘      要：Facing the very high-resolution( VHR) image classification problem,a feature extraction and fusion framework is presented for VHR panchromatic and multispectral image classification based on deep learning techniques. The proposed approach combines spectral and spatial information based on the fusion of features extracted from panchromatic( PAN) and multispectral( MS) images using sparse autoencoder and its deep version. There are three steps in the proposed method,the first one is to extract spatial information of PAN image,and the second one is to describe spectral information of MS image. Finally,in the third step,the features obtained from PAN and MS images are concatenated directly as a simple fusion feature. The classification is performed using the support vector machine( SVM) and the experiments carried out on two datasets with very high spatial resolution. MS and PAN images from WorldView-2 satellite indicate that the classifier provides an efficient solution and demonstrate that the fusion of the features extracted by deep learning techniques from PAN and MS images performs better than that when these techniques are used separately. In addition,this framework shows that deep learning models can extract and fuse spatial and spectral information greatly,and have huge potential to achieve higher accuracy for classification of multispectral and panchromatic images.