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An Effective Correction Method for Seriously Oblique Remote Sensing Images Based on Multi-View Simulation and a Piecewise Model

机译:基于多视角仿真和分段模型的严重倾斜遥感图像有效校正方法

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Conventional correction approaches are unsuitable for effectively correcting remote sensing images acquired in the seriously oblique condition which has severe distortions and resolution disparity. Considering that the extraction of control points (CPs) and the parameter estimation of the correction model play important roles in correction accuracy, this paper introduces an effective correction method for large angle (LA) images. Firstly, a new CP extraction algorithm is proposed based on multi-view simulation (MVS) to ensure the effective matching of CP pairs between the reference image and the LA image. Then, a new piecewise correction algorithm is advanced with the optimized CPs, where a concept of distribution measurement (DM) is introduced to quantify the CPs distribution. The whole image is partitioned into contiguous subparts which are corrected by different correction formulae to guarantee the accuracy of each subpart. The extensive experimental results demonstrate that the proposed method significantly outperforms conventional approaches.
机译:传统的校正方法不适用于有效校正在严重倾斜的情况下获得的遥感图像,该严重倾斜的情况具有严重的失真和分辨率差异。考虑到控制点的提取和校正模型的参数估计在校正精度中起着重要作用,本文介绍了一种有效的大角度(LA)图像校正方法。首先,提出了一种基于多视角仿真的新的CP提取算法,以确保参考图像和LA图像之间的CP对有效匹配。然后,使用优化的CP改进了新的分段校正算法,其中引入了分布测量(DM)的概念来量化CP的分布。整个图像被划分为连续的子部分,这些子部分将通过不同的校正公式进行校正,以保证每个子部分的准确性。广泛的实验结果表明,所提出的方法明显优于常规方法。

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