Multispectral and Panchromatic Data Fusion Assessment Without Reference

Abstract

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.

Pansharpening by Convolutional Neural Networks

“…For performance assessment, we use a number of metrics proposed in the literature, since no single one can be considered by itself as a reliable indicator of quality. In particular, besides several full-reference metrics, which measure performance on the reduced resolution dataset according to the Wald protocol, we consider also the no-reference QNR [44] and two derived metrics, that work on the full-resolution dataset. In fact, while these latter indicators may be considered less objective than the former, they are insensitive to possible scale-related phenomena.…”

Pansharpening using total variation regularization

“…SAM [16], ERGAS [5], Q4 [16] cannot be used. Therefore we adopt the QNR metric proposed in [17] to examine the quality of the fused image. The QNR can provide three indices: spectral distortion (D λ ), spatial distortion (D S ) and total quality (QNR).…”

Review and Performance Comparison of Pansharpening Algorithms for RASAT Images

“…To overcome this shortcoming, various approaches have been proposed in the literature for performance comparison purposes. The most widely accepted and utilized of these approaches is the Wald's protocol [37]. In Wald's protocol, which is also adopted in this work, the spatial resolution of the MS and PAN images are first reduced, and pan-sharpening methods are applied on these reduced resolution images.…”