Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/68706
Title: Method and device for classifying remote images by integrating space information and spectral information
Other Titles: 融合空间信息及光谱信息的遥感图像的分类方法及装置
Authors: Shi, WZ 
Miao, ZL 
Issue Date: 1-Apr-2015
Publisher: 中华人民共和国国家知识产权局
Source: 中国专利 ZL 201210003388.1 How to cite?
Abstract: The invention relates to a method and a device for classifying remote images by integrating space information and spectral information. The method includes the steps: performing pixel-wise support vector machine classification and area-based image segmentation for the remote images so as to obtain classified images and segmented images respectively; and combining the classified images with the segmented images, and performing majority voting so as to obtain final classified images. Since classified results of the remote images are obtained based on combination of the area-based image segmented results and the pixel-wise classified results, the method and the device are better in robustness, low in computing cost, easy to perform and capable of avoiding the problem of dimensional proportion selection. Besides, the defect that traditional partitional-clustering-segmentation-based classification of the hyperspectral images by integrating the space information and spectral information is non-robust is overcome.
本发明涉及一种融合空间信息及光谱信息的遥感图像的分类方法及装置,该方法包括对所述遥感图像分别执行逐像素的支持向量机分类以得到分类图像,和基于区域的图像分割处理以得到分割图像;将所述分类图像和分割图像组合并执行大多数一致表决处理,以得到最终的分类图像。将基于区域的图像分割结果和逐像素的分类结果相结合获得遥感图像的分类结果具有更好的稳健性,计算成本较低,易于执行及不产生尺寸比例的选择问题。解决了传统的融合基于划分聚类(Partitional Clustering)分割的高光谱图像的融合空间及光谱信息分类的不稳健的缺陷。
URI: http://hdl.handle.net/10397/68706
Rights: 专利权人: The Hong Kong Polytechnic University.
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