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首页> 外文期刊>International journal of image and data fusion >Effects of the spectral properties of a panchromatic image on pan-sharpening simulated using hyperspectral data
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Effects of the spectral properties of a panchromatic image on pan-sharpening simulated using hyperspectral data

机译:使用高光谱数据模拟的全色图像光谱特性对锐化的影响

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摘要

This study proposes a methodology for simulating pan-sharpening using hyperspectral (HS) data to evaluate the influence of the spectral properties (band position and band width) of panchromatic (PAN) data on the quality of pan-sharpened data. PAN images were generated from Airborne Visible/Infrared Imaging Spectrometer HS data by changing the position and width of the spectral waveband, and these images were subjected to pan-sharpening with multispec-tral (MS) bands, also generated from HS data. The qualities of pan-sharpened MS data were evaluated using five measures: erreur relative globale adimensionnelle de synthese, weighted signal-to-noise ratio, universal image quality index, quality index based on local variance and objective image fusion performance measure. This methodology was applied to three pan-sharpening methods (Gram-Schmidt spectral sharpening, block-based synthetic variable ratio and generalised Laplacian pyramid with spectral distortion minimisation) to characterise the spectral and spatial qualities of pan-sharpened images. The results show that the pan-sharpened images were affected by the spectral properties of the PAN data to varying degrees depending on the pan-sharpening method used and the land cover type. Better-quality images were obtained if the spectral properties of the PAN and MS bands were similar. No one spectral property was identified as best for all MS bands. This methodology will be helpful for the evaluation of the spectral behaviour of pan-sharpening methods, the development of new pan-sharpening methods and the design of new sensors suitable for pan-sharpening.
机译:这项研究提出了一种使用高光谱(HS)数据模拟泛锐化的方法,以评估全色(PAN)数据的光谱特性(波段位置和带宽)对泛锐化数据质量的影响。通过更改光谱波段的位置和宽度,从机载可见/红外成像光谱仪HS数据生成PAN图像,并对这些图像进行多光谱(MS)波段的全锐化处理,该波段也从HS数据生成。使用五种方法评估了全面锐化MS数据的质量:综合相对误差,加权信噪比,通用图像质量指标,基于局部方差的质量指标和客观图像融合性能指标。该方法被应用于三种泛锐化方法(Gram-Schmidt光谱锐化,基于块的合成可变比率和具有最小化频谱失真的广义拉普拉斯金字塔),以表征泛锐化图像的光谱和空间质量。结果表明,根据所使用的平锐化方法和土地覆盖类型,平锐化图像会受到PAN数据的光谱特性的不同程度的影响。如果PAN和MS波段的光谱特性相似,则可以获得质量更好的图像。没有一个光谱特性被确定为对所有MS波段均最佳。该方法将有助于评估全场锐化方法的光谱行为,开发新的全场锐化方法以及设计适合于全场锐化的新传感器。

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