With the rapid development of remote sensing technology, research on land use classification methods based on hyperspectral remote sensing images has attracted widespread attention. Existing land-use classification studies mostly use the average filtering method at a single scale for spectral image processing. These methods cannot accurately filter the window range, which leads to the neglect of image detail information, and the single kernel matrix cannot characterize multifeature information, resulting in reduced classification accuracy. Therefore, this study intended to use a superpixel segmentation method to perform multiscale superpixel segmentation on the first principal component of a hyperspectral image at multiple scales. By combining the weighted multiscale spatial-spectral kernel and the original spatial-spectral kernel to form a synthetic kernel for land use classification, the hyperspectral image of the National Mall in Washington DC was used as experimental data to test and analyze this method. The experimental results showed that the classification accuracy of this method on the experimental test set was 98.53%, which is compared with the classification results obtained by the single-scale spatial spectral synthetic nuclear method, the original spatial spectral synthetic nuclear method and the wavelength segmented synthetic nuclear method, the effective classification accuracy with this method was increased by 7.56%. The results prove that this method can effectively solve the problems of the lack of adaptability of the image spectrum and the lack of comprehensive spectral information and can significantly improve the accuracy of land use classification.

中文翻译：

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基于多尺度超像素的高光谱图像土地利用分类研究

随着遥感技术的飞速发展，基于高光谱遥感影像的土地利用分类方法的研究引起了广泛的关注。现有的土地利用分类研究大多使用单一尺度的平均滤波方法进行光谱图像处理。这些方法无法准确地过滤窗口范围，从而导致图像细节信息被忽略，并且单个核矩阵无法表征多特征信息，从而降低了分类精度。因此，本研究打算使用超像素分割方法对多光谱的高光谱图像的第一主成分执行多尺度超像素分割。通过将加权的多尺度空间光谱核与原始空间光谱核相结合，形成土地利用分类的合成核，以华盛顿特区国家购物中心的高光谱图像为实验数据，对该方法进行了测试和分析。实验结果表明，该方法在实验集上的分类精度为98.53％，与单尺度空间光谱合成核方法，原始空间光谱合成核方法和波长分段得到的分类结果相比较。合成核方法，该方法的有效分类精度提高了7.56％。