Visual quality is important for remote sensing data presented as grayscale, color or pseudo-color images. Although several visual quality metrics (VQMs) have been used to characterize such data, only a limited analysis of their applicability in remote sensing applications has been done so far. In this paper, we study correlation factors for a wide set of VQMs for color images with distortion types typical for remote sensing. It is demonstrated that there are many metrics that have very high Spearman rank order correlation, e.g. PSNR-based and SSIM-based metrics. Meanwhile, there are also metrics that are practically uncorrelated with others. A detailed analysis of VQMs that have the largest SROCC values and belong to different groups is presented in this paper.
Oleg Ieremeiev, Vladimir Lukin, Krzysztof Okarma, Karen Egiazarian, Benoit Vozel, "On properties of visual quality metrics in remote sensing applications" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems, 2022, pp 354-1 - 354-6, https://doi.org/10.2352/EI.2022.34.10.IPAS-354