使用基于核的图像滤波的智能泛锐化方法

Ahmad AL Smadi, Shuyuan Yang, Atif Mehmood, A. Abugabah, Min Wang, M. Bashir
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引用次数: 6

摘要

遥感图像融合在监测、计量、农业等领域有着广泛的应用。图像融合从多个图像源中收集基本信息,并将它们合并成一个图像,称为融合图像。融合后的图像包含了相关的数据,其信息量比从单一来源提取的任何其他图像都要大。本研究提出了一种基于图像滤波的泛锐化技术,利用双边滤波器从全色图像中生成高频细节。利用不同类型的侧窗引导滤波器对全色图像的多光谱波段进行增强,然后利用这些滤波器对图像组合时出现的空间数据偏差进行调整。实验结果表明,该方法在遥感数据的主客观评价方面与前人的研究结果基本一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart pansharpening approach using kernel-based image filtering
Remote sensing image fusion plays important roles in numerous applications, including monitoring, metrology, and agriculture. Image fusion gathers essential information from several image sources and consolidates them into a single image called a fused image. The fused image involves relevant data, and it is more informative than any other images extracted from one source. This study proposed a pansharpening technique based on image filtering utilising a bilateral filter to generate high-frequency details from panchromatic image. The various types of side window guided filters are employed to enhance the multispectral band from panchromatic image and then used these filters to adjust spatial data misfortune that happens when images are combined. Experimental results demonstrated that the proposed method provides consistent results concise with reported by the previ-ous research in terms of subjective and objective assessments on remote sensing data.
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