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An Efficient Mosaic Algorithm Considering Seasonal Variation: Application to KOMPSAT-2 Satellite Images

机译:考虑季节变化的高效镶嵌算法:在KOMPSAT-2卫星图像中的应用

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摘要

As the aerospace industry grows, images obtained from Earth observation satellites have been successfully used in various fields. Specifically, the demand for a high-resolution (HR) optical images is gradually increasing, and hence the generation of a high-quality mosaic image is being magnified as an interesting issue. In this paper, we have proposed an efficient mosaic algorithm for HR optical images that are significantly different due to seasonal change. The algorithm includes main steps such as: (1) seamline extraction from gradient magnitude and seam images; (2) histogram matching; and (3) image feathering. Eleven Kompsat-2 images characterized by seasonal variations are used for the performance validation of the proposed method. The results of the performance test show that the proposed method effectively mosaics Kompsat-2 adjacent images including severe seasonal changes. Moreover, the results reveal that the proposed method is applicable to HR optic images such as GeoEye, IKONOS, QuickBird, RapidEye, SPOT, WorldView, etc.
机译:随着航空航天业的发展,从地球观测卫星获得的图像已成功应用于各个领域。具体地,对高分辨率(HR)光学图像的需求逐渐增加,因此高质量马赛克图像的生成被放大为一个有趣的问题。在本文中,我们针对HR光学图像提出了一种有效的镶嵌算法,该算法由于季节变化而显着不同。该算法包括以下主要步骤:(1)从梯度幅度和接缝图像中提取接缝线; (2)直方图匹配; (3)图像羽化。十一张以季节变化为特征的Kompsat-2图像用于所提出方法的性能验证。性能测试结果表明,该方法有效拼接了Kompsat-2邻近图像,包括严重的季节变化。而且,结果表明,该方法适用于GeoEye,IKONOS,QuickBird,RapidEye,SPOT,WorldView等HR光学图像。

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