A No-Reference Spectral Quality Assessment Method for Multispectral Pansharpening

Multispectral pansharpening is a technique that produces the high-resolution (HR) multispectral (MS) images by fusing the spatial details of HR panchromatic (PAN) image with the spectral information of low-resolution MS images of the same scene. Due to the lack of HR reference images in reality, no-reference (NR) pansharpening quality assessment has always been a challenging research. Most of the current NR quality assessment methods mainly focus on the overall quality of pansharpened images, and there are few independent indexes for evaluating the spectral quality. In this paper, we propose a novel NR spectral quality assessment method based on the standard Benford's law, which assesses the spectral quality by extracting the first digit distribution (FDD) features of the angle components of the pansharpened images in the hyperspherical color domain (HCD). The experimental results demonstrate that our method is superior to some existing NR spectral distortion indexes.