Chapter 3
Quality Assessment of Fusion
3.1 Intro duction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.2 Quality Definition for Pansharpening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.2.1 Statistical Quality/Distortion Indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.2.1.1 Indices for scalar valued images . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.2.1.2 Indices for vector valued images . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.2.2 Protocols Established for Pansharpening . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.2.2.1 Wald’s protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.2.2.2 Zhou’s protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.2.2.3 QNR protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.2.2.4 Khan’s protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.2.3 Extension to Hyp erspectral Pansharpening . . . . . . . . . . . . . . . . . . . . . . . 61
3.2.4 Extension to Thermal V-NIR Sharpening . . . . . . . . . . . . . . . . . . . . . . . . 62
3.3 Assessment of Optical and SAR Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3.1 Introduction
Quality assessment of remote sensing image fusion has been, and still
is, the object of extensive research activities. Unlike fusion aimed at vi-
sion/detection/recognition purposes, like surveillance or for military applica-
tions, in which quality is mainly related to a subjective perception that may
be embodied by several statistical single-image indices, like contrast, gradi-
ents, entropy, and so on, remote sensing image fusion requires the definition
of more stringent and quantitative measurements that involve both original
images and fusion product images. Since the target of fusion is generally un-
available and thus cannot be used as reference, several protocols of quality
evaluation have been developed to overcome the lack of a reference.
Given two datasets, fusion aims at producing a third dataset that inher-
its some of the properties of its components. The quality of a fusion product
should be related to its consistency with the component datasets according to
the different properties that are inherited. In most cases, one of the datasets
involved in the fusion process features a spectral diversity. The different re-
sponse of the imaged scene in different intervals of wavelengths is responsible
for the spectral information. After fusion, at least in principle, it should be
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