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Automatic image registration based on plain objects detection and recognition in remote sensing tasks

机译:在遥感任务中基于普通物体检测和识别的自动图像配准

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摘要

Image registration is central problem to many tasks in digital image processing and therefore it has a vast range of applications. A scheme of automatic image registration based on plain objects detection and recognition in remote sensing tasks is presented in this paper. It relates to the concept of plain object in image and includes three subsystems. A subsystem of plain objects detection in image is based on a new method of plain objects detection in image. It relates to the land use classification process, different image segmentation methods and depends on the particular application. A subsystem of conjugate plain objects determination relate to a new method of plain objects recognition in images by shape based on stochastic geometry. It is invariant with respect to projective distortions. A subsystem of image registration determines an optimal geometric transformation and register given input images based on it. This paper reviews existing methods of image registration and emphasizes parametric, non-parametric and hybrid image registration techniques. Experimental results confirm the efficiency of the proposed system.
机译:图像配准是数字图像处理中许多任务的中心问题,因此它具有广泛的应用范围。提出了一种基于平面物体检测与识别的遥感任务自动图像配准方案。它涉及图像中的普通对象的概念,包括三个子系统。图像中的普通物体检测子系统是基于一种新的图像中普通物体检测方法。它涉及土地利用分类过程,不同的图像分割方法,并取决于特定的应用。共轭平面物体确定子系统涉及一种基于随机几何形状的形状识别图像中平面物体的新方法。对于投影失真,它是不变的。图像配准子系统确定最佳几何变换,并基于该子系统对给定的输入图像进行配准。本文回顾了现有的图像配准方法,重点介绍了参数,非参数和混合图像配准技术。实验结果证实了该系统的有效性。

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