Pan-sharpened images can effectively be used in various remote sensing applications. During recent years a vast
number of pan-sharpening algorithms has been proposed. Thus, the evaluation of their performance became a
vital issue. The quality assessment of pan-sharpened images is complicated by the absence of reference data, the
ideal image what the multispectral scanner would observe if it had as high spatial resolution as the panchromatic
instrument. This paper presents a novel method to evaluate the degree of local quality degradation in pansharpened
images, which is the result of contrast inversion of the fusing bands. The proposed method does
not require a reference image. Firstly, the algorithm identifies the areas in which the contrast inversion may
be confidently detected. Then, based on the found spatial consistency violations, the quantitative degradation
index is calculated for the fused product. The proposed approach was validated with the use of very high
resolution optical imagery. The experiments have shown that the proposed measure objectively reflects local
quality deterioration of pan-sharpened images.
This paper presents the results of the investigation on image fusion applied to data with significantly different spectral
properties. The experiments with simulated and real data show that conventional fusion methods heavily distort
geometrical shapes of features in case of fusion of data with different spectral characteristics. As a step forward to solve
the problem, a novel fusion approach is proposed. The method uses the relationship between the Wavelet Transform
Modulus Maxima (WTMM) corresponding to the same feature in the fusing images. The experiments showed
advantages of the proposed method in areas of substantially dissimilar spectral characteristics of merging data. The
found limitations of the method are discussed as well.
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