Abstract
Abstract. In this paper results from the evaluation of several state-of-the-art pansharpening techniques are presented for the VNIR and SWIR bands of Sentinel-2. A procedure for the pansharpening is also proposed which aims at respecting the closest spectral similarities between the higher and lower resolution bands. The evaluation included 21 different fusion algorithms and three evaluation frameworks based both on standard quantitative image similarity indexes and qualitative evaluation from remote sensing experts. The overall analysis of the evaluation results indicated that remote sensing experts disagreed with the outcomes and method ranking from the quantitative assessment. The employed image quality similarity indexes and quantitative evaluation framework based on both high and reduced resolution data from the literature didn’t manage to highlight/evaluate mainly the spatial information that was injected to the lower resolution images. Regarding the SWIR bands none of the methods managed to deliver significantly better results than a standard bicubic interpolation on the original low resolution bands.
Highlights
Fusing effectively spatial and spectral information from different image modalities is a critical and valuable tool for numerous applications in geoscience, remote sensing, image analysis and computer vision
Among the several fusion techniques, pansharpening is a critical one, which focused on the injection of spatial information, extracted from a high resolution panchromatic (PAN) band, to other, with lower spatial resolution, multispectral (MS) ones
For the Full Resolution (FR) experiment, QNR index was utilized, while the quality assessment for the Reduced Resolution (RR) experiment was carried out using the robust Q4 index [Garzelliand Nencini, 2009, Vivone et al, 2015]
Summary
Fusing effectively spatial and spectral information from different image modalities is a critical and valuable tool for numerous applications in geoscience, remote sensing, image analysis and computer vision. Among the several fusion techniques, pansharpening is a critical one, which focused on the injection of spatial information, extracted from a high resolution panchromatic (PAN) band, to other, with lower spatial resolution, multispectral (MS) ones. Early research efforts which employed LANDSAT and SPOT satellite imagery focused on defining efficient quantitative evaluation tools towards deciding among several techniques for the optimal one [Gillespie et al, 1987, Chavez et al, 1991, Wald et al, 1997]. Methods based on the multi-resolution analysis are focusing on defining the optimal way the missing highpass information will be injected on the lower resolution image [Chavez et al, 1991, Otazu et al, 2005, Aiazzi et al, 2006, Vivone et al, 2014]
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