Harmonization of Multispectral and Panchromatic Images From VHR/EHR Spaceborne Scanners

This study presents a new concept related to the quality and usability of multispectral (MS) and panchromatic (PAN) datasets captured by very/extremely high-resolution (VHR/EHR) satellite MS scanners. Despite the ever-increasing resolution and spectral coverage capabilities of modern instruments, MS datasets suffer from the presence of aliasing originating from the insufficient sampling step size, corresponding to a high value of the modulation transfer function (MTF) of the instrument at the Nyquist frequency. Another source of degradation is the local misalignment between interpolated MS and PAN, originating from different viewpoints along the orbit of the instruments in the presence of discontinuities of the imaged surface. Here, we propose a procedure to harmonize MS and PAN datasets: aliasing artifacts of MS are suppressed; local MS-to-MS and MS-to-PAN shifts are damped. This is feasible for the unimodality of the MS and PAN instruments. Harmonization of MS toward PAN is achieved by injecting the least-squares (LS) residue of the multivariate linear regression of the interpolated bands captured by each MS scanner toward the low-pass-filtered PAN. Experiments with two (MS-PAN) and three (MS1-MS2-PAN) onboard instruments show that an almost perfect alignment and a significant reduction of aliasing patterns are achieved. MS pansharpening greatly benefits from harmonized datasets. When the latter are used for the fusion and as indicators of spectral and spatial qualities of fusion products, inconsistencies noticed and complained about in the literature vanish. The procedure is in real time, fully automated, and does not require additional or ancillary information.