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To assess the performance of image quality metrics (IQMs), some regressions, such as logistic regression and polynomial regression, are used to correlate objective ratings with subjective scores. However, some defects in optimality are shown in these regressions. In this correspondence, monotonic regression (MR) is found to be an effective correlation method in the performance assessment of IQMs. Both theoretical analysis and experimental results have proven that MR performs better than any other regression. We believe that MR could be an effective tool for performance assessment in the IQM research.

This paper performed the fusion test using high resolution TerraSAR and ALOS optical multi-spectral image in Hengduan mountains area. The results of automatic classification compared to the visual effect for fusion image indicated that the classification accuracy by HPF is better than other fusion algorithm, which are superior to HPF in other application.

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