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Comparison of Methods for IKONOS Images Pan-sharpening Using Synthetic Sensors

机译:使用合成传感器对IKONOS图像进行全景锐化的方法比较

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摘要

Many methods are present in literature for pan-sharpening of satellite images: they permit to transfer geometric resolution of panchromatic data to multispectral ones, but the results of their application are different. To evaluate the quality of these products, visual analysis is carried out, above all on the RGB composition to detect colour distortion. To quantize the level of similarity of the pan-sharpened images with them that should be achieved with effective more effective sensors, several indices are available such as: RMSE, correlation coefficients, UIQI, RASE. The principal limit of these indices consists in the terms of comparison because they compare the pan-sharpened images with the original ones that are with lower resolution. To supply the unavailability of the effective dataset with the same pixel dimensions of the pan-sharpened files, synthetic sensors can be introduced with lower resolution than the original ones. The correspgndent degraded images can be submitted to pan-sharpening process and the results can be considered performed if similar to the original multispectral dataset. In this study IKONOS synthetic sensors are introduced to compare different methods: transforming the digital numbers into the radiance of the earth surface, original images of Campania Region are degraded and then submitted to some pan-sharpening approaches. The following methods are considered: multiplicative, simple mean, IHS, Fast IHS, Brovey, Weighted Brovey, Gram Schmidt, Zhang. Each resulting dataset is compared with the original multispectral one to evaluate the performance of each method.
机译:文献中提供了许多方法来使卫星图像进行全锐化:它们允许将全色数据的几何分辨率转换为多光谱数据,但是其应用结果不同。为了评估这些产品的质量,首先对RGB组成进行了视觉分析,以检测颜色失真。为了量化应使用有效的更有效传感器实现的全锐化图像与它们的相似度,可以使用几个指标,例如:RMSE,相关系数,UIQI,RASE。这些索引的主要限制在于比较项,因为它们将泛锐化的图像与分辨率较低的原始图像进行比较。为了提供与全锐化文件相同的像素尺寸的有效数据集的不可用性,可以引入分辨率比原始传感器低的合成传感器。如果与原始多光谱数据集相似,则可以将相应的降级图像提交至全锐化处理,并且可以认为结果已执行。在这项研究中,介绍了IKONOS合成传感器以比较不同的方法:将数字转换为地球表面的辐射度,将坎帕尼亚地区的原始图像降级,然后进行泛锐化处理。考虑以下方法:乘法,简单均值,IHS,快速IHS,Brovey,加权Brovey,Gram Schmidt,Zhang。将每个结果数据集与原始多光谱数据集进行比较,以评估每种方法的性能。

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