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提出了一种基于支持向量机的遥感影像薄云去除方法。利用支持向量机对边缘点的极强捕捉能力,将含云遥感影像进行多尺度分解,获得不同尺度上的变换系数,再结合方向滤波器组得到丰富的高频信息。采用自适应阈值的图像增强方法处理这片区域,重构时通过对高频区域的增强和低频区域的抑制,得到去云图像。实验结果表明,采用该方法能有效地去除遥感影像中的薄云。 相似文献
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In our study,support vector value contourlet transform is constructed by using support vector regression model and directional filter banks.The transform is then used to decompose source images at multi-scale,multi-direction and multi-resolution.After that,the super-resolved multi-spectral image is reconstructed by utilizing the strong learning ability of support vector regression and the correlation between multi-spectral image and panchromatic image.Finally,the super-resolved multi-spectral image and the panchromatic image are fused based on regions at different levels.Our experiments show that,the learning method based on support vector regression can improve the effect of super-resolution of multi-spectral image.The fused image preserves both high space resolution and spectrum information of multi-spectral image. 相似文献
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支持向量机回归模型的性能与所选用的损失函数有很大关系.本文提出一种具分段损失函数的支持向量机回归模型,其分段损失函数对落在不同区间的误差项采用不同的惩罚函数形式,并将该模型应用于投资决策问题中,估计收益率向量的联合概率密度函数和最优投资组合.仿真实验表明,其性能要优于一般的支持向量回归方法. 相似文献
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