CAJ | 학술논문

遥感图像分类是遥感图像分析和理解的基础，是遥感图像研究中的重要内容之一。为提高分类效果，遥感图像分类中通常需要综合运用多种特征。提出一个新的基于特征级融合的遥感图像分类方法。将多种图像空间特征和光谱特征分别作为分类器的输入，将各分类器的概率输出拼接起来作为中间层特征再进行分类。该方法有效避免了多特征直接拼接存在的尺度问题。在In-dian93和Flightline C1两个数据集上的实验结果表明该方法具有一定优势。
요감도상분류시요감도상분석화리해적기출，시요감도상연구중적중요내용지일。위제고분류효과，요감도상분류중통상수요종합운용다충특정。제출일개신적기우특정급융합적요감도상분류방법。장다충도상공간특정화광보특정분별작위분류기적수입，장각분류기적개솔수출병접기래작위중간층특정재진행분류。해방법유효피면료다특정직접병접존재적척도문제。재In-dian93화Flightline C1량개수거집상적실험결과표명해방법구유일정우세。
As the basis of remote sensing image analysis and comprehension, remote sensing image classification is one of the main topics in remote sensing image research.To improve classification effect, the integrated use of multiple features is usually required in the classifica-tion.In this paper, we propose a new classification method which is based on feature level data fusion.After extracting the multiple image space features and spectral features, we feed each type of feature into classifiers.The probability outputs of these classifiers are jointed to form the middle level features, and the classification is applied once again.The method effectively avoids the scale problem in direct conjunction of multiple features.Experiments on two classical data sets, that is, Indian93 and Flightline C1, show that the method has obvious advantage.