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Transformation-invariant extraction of multi-location image features from remote sensing imagery

机译:遥感影像中多位置图像特征的变换不变提取

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A novel method of transformation-invariant feature extraction called multi-location saliency pattern is proposed in this paper for object recognition and image matching. Multi-location image features are extracted in salient image points, which indicate image locations with high intensity contrast, region homogeneity and shape saliency. Three distinctive types of fragment descriptors are extracted to form the descriptor vector: pose, regional shape, and intensity (texture) descriptors. Pose characteristics and regional shape descriptors are made invariant to image similarity transformations.
机译:提出了一种新的变换不变特征提取方法,称为多位置显着性模式,用于目标识别和图像匹配。在显着的图像点中提取多位置图像特征,这些图像点指示具有高强度对比度,区域均匀性和形状显着性的图像位置。提取三种不同类型的片段描述符以形成描述符向量:姿势,区域形状和强度(纹理)描述符。使姿势特征和区域形状描述符对于图像相似性变换而言是不变的。

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