遥感图像包含了大量的地理信息和反映地理特征和空间结构的复杂度。
Remote sensing images contain huge amount of geographical information and reflect the complexity of geographical features and spatial structures.
针对遥感图像配准，基于尺度不变特征变换(SIFT)提出了一种在核空间中构建仿射不变描述子的方法。
A technique to construct an affine invariant descriptor for remote-sensing image registration based on the scale invariant features transform (SIFT) in a kernel space is proposed.
基于图像特征的遥感图像信息融合是在突出目标地物的空间结构和纹理特征基础上的信息融合。
The image feature fusion is a kind of data fusion that is based on spectral structure and texture feature of the objects.
基于图像特征的遥感图像信息融合是在突出目标地物的空间结构和纹理特征情况下的信息融合。
The image feature fusion is a kind of data fusion that is based upon spectral structure and texture feature of the objects.
提出了一种利用图像特征空间信息的核函数——层次对数极坐标匹配核，用于遥感图像建筑物目标的分类。
This paper proposes a kernel function - hierarchical log-polar matching kernel which making use of the feature spatial information for building classification in remote sensing images.
提出了一种利用图像特征空间信息的核函数——层次对数极坐标匹配核，用于遥感图像建筑物目标的分类。
This paper proposes a kernel function - hierarchical log-polar matching kernel which making use of the feature spatial information for building classification in remote sensing images.
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