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Pansharpening Quality Assessment Using the Modulation Transfer Functions of Instruments

机译：使用仪器的调制传递函数进行泛锐化质量评估

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摘要

Quality assessment of pansharpening methods is not an easy task. Quality-assessment indexes, like Q4, spectral angle mapper, and relative global synthesis error, require a reference image at the same resolution as the fused image. In the absence of such a reference image, the quality of pansharpening is assessed at a degraded resolution only. The recently proposed index of Quality Not requiring a Reference (QNR) is one among very few tools available for assessing the quality of pansharpened images at the desired high resolution. However, it would be desirable to cross the outcomes of several independent quality-assessment indexes, in order to better determine the quality of pansharpened images. In this paper, we propose a method to assess fusion quality at the highest resolution, without requiring a high-resolution reference image. The novel method makes use of digital filters matching the modulation transfer functions (MTFs) of the imaging-instrument channels. Spectral quality is evaluated according to Wald's spectral consistency property. Spatial quality measures interscale changes by matching spatial details, extracted from the multispectral bands and from the panchromatic image by means of the high-pass complement of MTF filters. Eventually, we highlight the necessary and sufficient condition criteria for quality-assessment indexes by developing a pansharpening method optimizing the QNR spatial index and assessing the quality of fused images by using the proposed protocol.
机译：锐化方法的质量评估并非易事。像Q4，光谱角度映射器和相对全局综合误差之类的质量评估指标需要参考图像的分辨率与融合图像的分辨率相同。在没有这样的参考图像的情况下，仅在降低的分辨率下评估全景清晰度的质量。最近提出的不需要参考的质量（QNR）索引是极少数可用于以所需的高分辨率评估锐化图像质量的工具之一。然而，希望更好地交叉几个独立的质量评估指标的结果，以便更好地确定锐化图像的质量。在本文中，我们提出了一种在不需要高分辨率参考图像的情况下以最高分辨率评估融合质量的方法。该新颖方法利用了与成像仪器通道的调制传递函数（MTF）匹配的数字滤波器。根据Wald的光谱一致性属性评估光谱质量。空间质量通过匹配空间细节来度量尺度间变化，空间细节是通过MTF滤镜的高通补码从多光谱带和全色图像中提取的。最终，我们通过开发一种优化QNR空间指数的泛锐化方法并通过使用所提出的协议评估融合图像的质量，突出了质量评估指标的必要条件和充分条件。

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