RASAT图像的泛锐化算法综述及性能比较

S. Kahraman, A. Erturk
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引用次数: 9

摘要

本研究通过考虑17种应用于RASAT卫星图像的泛锐化算法,对泛锐化方法进行了最广泛的性能比较。RASAT是土耳其设计和制造的第一颗地球观测卫星。包括来自不同类别的标准和最先进的泛锐化方法,例如组件替换(CS),基于调制(MB),多分辨率分析(MRA)以及混合和变分方法,以便更好地了解和执行各种泛锐化方法的性能进行全面分析。实验验证程序按Wald方案设计,并根据7项定量评价标准进行定性和定量评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review and Performance Comparison of Pansharpening Algorithms for RASAT Images
This study presents the most extensive performance comparison of pansharpening methodologies by considering 17 pansharpening algorithms that are applied to the satellite images obtained from RASAT, which is the first earth observation satellite designed and manufactured in Turkey. Standard and state-of-the-art pansharpening approaches from various categories, such as component substitution (CS), modulation based (MB), multiresolution analysis (MRA), and hybrid and variational methods, are included in order to gain a better insight and perform a thorough analysis of the performance of various pansharpening methods. The experimental validation procedure was designed according to Wald's protocol, and the performance evaluations were conducted both qualitatively and quantitatively on the basis of seven quantitative evaluation criteria.
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