STRUCTURAL HIGH-RESOLUTION SATELLITE IMAGE INDEXING
STRUCTURAL HIGH-RESOLUTION SATELLITE IMAGE INDEXING
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发表时间：
2010-07
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通讯作者：
Gui-Song Xia;Wen Yang;J. Delon;Y. Gousseau;Hong Sun;H. Maître
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作者：
Gui-Song Xia;Wen Yang;J. Delon;Y. Gousseau;Hong Sun;H. Maître
高空间分辨率的卫星图像在图像理解和模式识别方面提出了许多具有挑战性的问题。首先，它们允许测量可能高达0.5米的小物体，同时出现纹理和几何结构。第二，同一类型场景中的物体可能以不同的尺度和方向出现。因此，图像索引方法应联合收割机图像的结构和纹理信息，并遵循一定的不变性质。本文对高分辨率卫星图像的索引问题进行了研究。我们提出了一种依赖于地形图的卫星图像索引方法（Caselles等人，1999）和基于形状的图像索引方案（Xia等人，2009年）。该方法既包含了卫星图像的纹理和结构信息，也对尺度、方向和对比度的变化具有鲁棒性。在一个真实的卫星图像数据库上的实验分析证实了该方法的有效性。
Satellite images with high spatial resolution raise many challenging issues in image understanding and pattern recognition. First, they allow measurement of small objects maybe up to 0.5 m, and both texture and geometrical structures emerge simultaneously. Second, objects in the same type of scenes might appear at different scales and orientations. Consequently, image indexing methods should combine the structure and texture information of images and comply with some invariant properties. This paper contributes to the indexing of high-resolution satellite images. We suggest a satellite image indexing method relying on topographic maps (Caselles et al., 1999) and a shape-based image indexing scheme (Xia et al., 2009). The proposed approach contains both the textural and structural information of satellite images and is also robust to changes in scale, orientation and contrast. Experimental analysis on a real satellite image database confirms the efficiency of the approach.