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A hybrid classification method using spectral, spatial, and textural features for remotely sensed images based on morphological filtering

机译:一种基于形态过滤的光谱,空间和纹理特征的混合分类方法

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"HYCLASS", a new hybrid classification method for remotely sensed multi-spectral images is proposed. This method consists of two procedures, the textural edge detection and texture classification. In the textural edge detection, the maximum likelihood classification (MLH) method is employed to find "the spectral edges", and the morphological filtering is employed to process the spectral edges into "the textural edges" by sharpening the opened curve parts of the spectral edges. In the texture classification, the supervised texture classification method based on normalized Zernike moment vector that the authors have already proposed. Some experiments using a simulated texture image and an actual airborne sensor image are conducted to evaluate the classification accuracy of the HYCLASS. The experimental results show that the HYCLASS can provide reasonable classification results in comparison with those by the conventional classification method.
机译:“Hyclass”,提出了一种用于远程感测多光谱图像的新的混合分类方法。该方法包括两个程序,纹理边缘检测和纹理分类。在纹理边缘检测中,采用最大似然分类(MLH)方法来查找“光谱边缘”,并且通过锐化光谱的打开的曲线部分来使用形态滤波来处理光谱边缘进入“纹理边缘”边缘。在纹理分类中,基于作者已经提出的标准化Zernike矩载体的监督纹理分类方法。使用模拟纹理图像和实际空气传感器图像进行一些实验以评估Hyclass的分类精度。实验结果表明,随着传统分类方法的比较,Hyclass可以提供合理的分类结果。

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