Pansharpening with transform‐based gradient transferring model

Abstract

As one of the most popular kinds of the component substitution (CS)-based pansharpening methods, the intensity-hue-saturation (IHS) method can produce the pan-sharpened images with high spatial quality while causing some spectral distortion, mainly owing to it cannot estimate an accurate intensity image in the IHS space. To solve this issue in the IHS method, in this study, the authors propose a new pansharpening method with gradient transferring in the generalised IHS transform space, which aims at estimating a more accurate intensity image. More specifically, the novelty of the proposed method consists of building a novel variational gradient transferring model to transfer the spatial gradient information of the panchromatic image into the new intensity image as well as preserve the local spectral information from the low resolution multispectral image. Finally, they compare the proposed method with some CS methods using the Pleiades, QuickBird, and GeoEye-1 satellite datasets from both the subjective and objective aspects. Specifically, the experimental results show that the proposed method yields better pansharpening results than the other methods in terms of higher spatial and spectral qualities.