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-  2016 

利用小波核最小噪声分离进行高光谱影像SVM分类
SVM Classification of Hyperspectral Image Based on Wavelet Kernel Minimum Noise Fraction

DOI: 10.13203/j.whugis20140209

Keywords: 高光谱影像,图像分类,核函数,最小噪声分离变换,
hyperspectral
,hyperspectral classification,kernel method,minimum noise fraction

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Abstract:

针对高光谱遥感影像线性特征提取方法在一定程度上会降低地物类别的可分性问题,在最小噪声分离变换基础上引入核方法,以小波核函数代替传统核函数,并将新型核最小噪声分离方法与支持向量机方法相结合,对高光谱影像数据进行分类。实验结果表明,基于小波核最小噪声分离变换的方法适合于高光谱遥感影像的非线性特征,将其应用于HYDICE系统与AVIRIS系统所获得的实验数据集,与对照算法相比,总体分类精度可提高3%~9%

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