Development of Multi-Strip Image Mosaicking for KOMPSAT-3A Images

Jong-Hwan Son, Sumin Park, Hyeon-Ju Ban, Taejung Kim
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Abstract

Abstract. High-resolution satellite imagery has a limitation in terms of coverage area. This limitation presents challenges for extensive-scale analysis at regional or national levels. To maximize the utility of high-resolution satellite imagery, the implementation of image mosaicking techniques is essential. In this paper, we have developed seamline extraction techniques and relative geometric correction optimized for high-resolution satellite imagery. Ultimately, we proposed a multi-strip image mosaicking method for KOMPSAT-3A (Korea Multi-Purpose Satellite-3A) images. We applied the Dijkstra's shortest path algorithm to efficiently extract seamlines. we also performed image registration based on feature matching and homography transformation to correct the relative geometric errors between input images. We conducted experiments with our methods using 29 scenes from KOMPSAT-3A L1G data. The results indicated high relative geometric accuracy, with an average error of 1.63 pixels. Furthermore, we were able to obtain high-quality seamless mosaic images. Our proposed method is expected to enhance the utility of KOMPSAT-3A imagery for large-scale environmental and urban analysis and to provide more accurate and comprehensive data.
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为 KOMPSAT-3A 图像开发多条图像镶嵌技术
摘要高分辨率卫星图像在覆盖面积方面存在局限性。这种局限性给区域或国家层面的大范围分析带来了挑战。为了最大限度地利用高分辨率卫星图像,必须采用图像镶嵌技术。在本文中,我们开发了针对高分辨率卫星图像的缝线提取技术和相对几何校正技术。最终,我们为 KOMPSAT-3A(韩国多用途卫星-3A)图像提出了一种多条图像镶嵌方法。我们还基于特征匹配和同形变换进行了图像配准,以纠正输入图像之间的相对几何误差。我们使用 KOMPSAT-3A L1G 数据中的 29 个场景对我们的方法进行了实验。结果表明,相对几何精度很高,平均误差为 1.63 像素。此外,我们还获得了高质量的无缝马赛克图像。我们提出的方法有望提高 KOMPSAT-3A 图像在大规模环境和城市分析中的实用性,并提供更准确、更全面的数据。
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