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Automatic satellite image georeferencing using a contour-matching approach

机译:使用轮廓匹配方法自动进行卫星图像地理配准

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Multitemporal and multisatellite studies or comparisons between satellite data and local ground measurements require nowadays precise and automatic geometric correction of satellite images. This paper presents a fully automatic geometric correction system capable of georeferencing satellite images with high accuracy. An orbital prediction model, which provides initial earth locations, is combined with the proposed automatic contour-matching technique. This combination allows correcting the low-frequency error component, mainly due to timing and orbital model errors, as well as the high-frequency error component, due to variations in the spacecraft's attitude. The approach aims at exploiting the maximum reliable information in the image to guide the matching algorithm. The contour-matching process has three main steps: 1) estimation of the gradient energy map (edges) and detection of the cloudless (reliable) areas; 2) initialization of the contours positions; 3) estimation of the transformation parameters (affine model) using a contour optimization approach. Three different robust and automatic algorithms are proposed for optimization, and their main features are discussed. Finally, the performance of the three proposed algorithms is assessed using a new error estimation technique applied to Advanced Very High Resolution Radiometer (AVHRR), Sea-viewing Wide Field of view Sensor (SeaWiFS), and multisensor AVHRR-SeaWiFS imagery.
机译:如今,多时相和多卫星研究或卫星数据与本地地面测量之间的比较需要对卫星图像进行精确和自动的几何校正。本文提出了一种全自动几何校正系统,该系统能够高精度地对卫星图像进行地理配准。提供初始地球位置的轨道预测模型与提出的自动轮廓匹配技术相结合。这种组合允许校正主要由于定时和轨道模型误差而引起的低频误差分量,以及由于航天器姿态的变化而引起的高频误差分量。该方法旨在利用图像中的最大可靠信息来指导匹配算法。轮廓匹配过程包括三个主要步骤:1)估计梯度能量图(边缘)和检测无云(可靠)区域; 2)初始化轮廓位置; 3)使用轮廓优化方法估计变换参数(仿射模型)。提出了三种不同的鲁棒和自动算法进行优化,并讨论了它们的主要特征。最后,使用一种应用于高级超高分辨率辐射计(AVHRR),海景宽视场传感器(SeaWiFS)和多传感器AVHRR-SeaWiFS图像的新误差估计技术,评估了三种算法的性能。

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