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Evaluation of various pansharpening methods using image quality metrics

机译:使用图像质量指标评估各种泛散山化方法

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The pansharpening has been a wide area of interest during these days because of its applications in remote sensing, geoscience. Day by day it is going deep, vast and interesting as well. The concept arises due to the fact that data provided by most earth observation satellites such as Ikonos, geoeye, quickbird and wordview2 are composed of several channels of multispectral image and single channel of panchromatic image. The pansharpening is derived from the fusion of these two images, which actually combines the characteristics of these two images. The image quality metrics provide the information about the special and spectral quality of the image. These special and spectral qualities are provided by the panchromatic and multispectral image. Most of the existing pan-sharpening quality assessment methods consider only the spectral quality and there are just few inventions which concentrate on these spatial characteristics. This paper presents a novel approach for spatial quality evaluation of pan-sharpening in high resolution satellite imagery. Obtained results clearly show the wide spatial discrepancy in quality of Pan-sharpened images, resulting from various pan-sharpening fusion methods which confirm the need for spatial quality valuation of fused products.
机译:由于其在遥感,地球科学的应用,Pansharpening在这几天中是广泛的兴趣领域。日复一日,它也会深入,巨大而有趣。由于大多数地球观测卫星提供的数据,例如ikonos,Geoeye,Quickbird和WordView2的数据由多光谱图像和单色图像的单个通道组成,因此该概念由于大多数地球观测卫星提供的数据而提供。 Pansharpening源自这两个图像的融合,其实际上结合了这两个图像的特征。图像质量指标提供了有关图像的特殊和光谱质量的信息。这些特殊和光谱素质由全色和多光谱图像提供。大多数现有的泛锐化质量评估方法仅考虑光谱质量,并且只有很少的发明,其集中在这些空间特征上。本文介绍了高分辨率卫星图像泛锐化的空间质量评价的新方法。获得的结果清楚地表明了泛尖锐的图像质量的宽空间差异,由各种泛锐化融合方法产生,该方法确认了融合产品的空间质量估值的需要。

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