The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
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allowed digital number range of the file) do not change
image quality for remote sensing applications.
• Visual evaluation results can be strongly
influenced by image display conditions. The same image
can be interpreted as having different qualities, if the
display conditions are not the same. Therefore, it is
important to assure a consistent display condition for
images compared to achieve a convincing visual
comparison result.
• Significant disagreement exists in the
quantitative measurements of the seven indicators.
Images having the same quality for remote sensing
applications are indicated as having significant quality
difference. This proves that the indicators are not
capable of providing convincing image similarity
measurements.
In the image fusion quality evaluation by Alparone et al.,(2004),
the SYN result is clearly the best according to the Q4, SAM and
CC measurements, as well as the visual comparison. Although
the SYN result does not have the best ERGAS value, it should
not be overly concerned because according to Alparone et
al.,(2004) ERGAS failed in measuring spectral distortion.
However, in the final ranking of Alparone et al.,(2004), the
authors’ fusion algorithms GLP-SDM and GLP-CBD were
ranked as the best, instead of the SYN results. This
demonstrated that the authors themselves did not trust the
measurement values, and personal preference played an
important role in the ranking.
In the fusion quality evaluation of the IEEE GRSS 2006 Data
Fusion Contest, the inconsistency and irregularity of the
evaluation has suggested the difficulty of using the seven
quantitative indicators to provide convincing quality
measurements. Otherwise, there would have been no need to be
selective in the contest evaluation for showing that the judge’s
GLP-CBD algorithm was the best and first class in the fusion
contest, and the obvious, misfused patches or areas would have
been detected.
In conclusion, the discrepancy between the visual evaluations
and quantitative analyses in the three cases discussed in this
paper demonstrate that the seven quantitative indicators (MB,
VD, SDD, CC, SAM, ERGAS, and Q4) cannot provide reliable
measurements for quality or similarity assessment between
remote sensing images.
ACKNOWLEDGEMENTS
The author thanks Mr. Z. Xiong and Mr. J. D. Mtamakaya for
their kind support in data and material preparation. The author
also thanks the City of Fredericton, NB, Canada, for providing
the original Ikonos Pan and MS images, and the IEEE GRSS
2006 data fusion contest committee for the original QuickBird
Pan and MS images.
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