This paper introduces a novel approach for evaluating the quality of pansharpened multispectral (MS) imagery without resorting to reference originals. Hence, evaluations are feasible at the highest spatial resolution of the panchromatic (PAN) sensor. Wang and Bovik's image quality index (QI) provides a statistical similarity measurement between two monochrome images. The QI values between any couple of MS bands are calculated before and after fusion and used to define a measurement of spectral distortion. Analogously, QI values between each MS band and the PAN image are calculated before and after fusion to yield a measurement of spatial distortion. The rationale is that such QI values should be unchanged after fusion, i.e., when the spectral information is translated from the coarse scale of the MS data to the fine scale of the PAN image. Experimental results, carried out on very high-resolution Ikonos data and simulated Pléiades data, demonstrate that the results provided by the proposed approach are consistent and in trend with analysis performed on spatially degraded data. However, the proposed method requires no reference originals and is therefore usable in all practical cases.

No abstract

No abstract

This letter focuses on quality assessment of fusion of multispectral (MS) images with high-resolution panchromatic (Pan) observations. A new quality index suitable for MS imagery having four spectral bands is defined from the theory of hyper-complex numbers, or quaternions. Both spectral and radiometric distortion measurements are encapsulated in a unique measurement, simultaneously accounting for local mean bias, changes in contrast, and loss of correlation of individual bands, together with spectral distortion. Results are presented and discussed on very high-resolution QuickBird data, through comparisons between state-of-the-art and advanced MS+ Pan merge algorithms

This letter presents a novel image quality index which extends the Universal Image Quality Index for monochrome images to multispectral and hyperspectral images through hypercomplex numbers. The proposed index is based on the computation of the hypercomplex correlation coefficient between the reference and tested images, which jointly measures spectral and spatial distortions. Experimental results, both from true and simulated images, are presented on spaceborne and airborne visible/infrared images. The results prove accurate measurements of inter- and intraband distortions even when anomalous pixel values are concentrated on few bands