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Target localization by least squares image matching including the deconvolution of image blur

机译:通过最小二乘图像匹配(包括图像模糊反卷积)进行目标定位

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Abstract: For many applications in photogrammetry precise target localization is essential. Target localization by image processing is composed of several steps, from target detection to fine centering at the end of the process. The following paper describes a model for fine centering of a target based on Least Squares Image Matching (LSM). Since the image of a target has been convoluted by the image sensor LSM has to be extended by an appropriate mathematical model. Its derivation, together with practical results for fiducial marks (circles and crosses) and targets that are circular in object space, are presented. !6
机译:摘要:对于摄影测量学中的许多应用,精确的目标定位至关重要。通过图像处理进行目标定位包括几个步骤,从目标检测到过程结束时的精确居中。以下论文描述了一种基于最小二乘图像匹配(LSM)的目标精确居中模型。由于目标图像已被图像传感器卷积,因此必须通过适当的数学模型来扩展LSM。介绍了它的推导,以及基准标记(圆形和十字形)和在对象空间中为圆形的目标的实际结果。 !6

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