Computer Science > Computer Vision and Pattern Recognition
[Submitted on 13 Aug 2021 (v1), last revised 4 Apr 2022 (this version, v3)]
Title:Full-resolution quality assessment for pansharpening
View PDFAbstract:A reliable quality assessment procedure for pansharpening methods is of critical importance for the development of the related solutions. Unfortunately, the lack of ground-truths to be used as guidance for an objective evaluation has pushed the community to resort to two approaches which can also be jointly applied. Hence, two kinds of indexes can be found in the literature: i) reference-based reduced-resolution indexes aimed to assess the synthesis ability; ii) no-reference subjective quality indexes for full-resolution datasets aimed to assess spectral and spatial consistency. Both reference-based and no-reference indexes present critical shortcomings which motivate the community to explore new solutions. In this work, we propose an alternative no-reference full-resolution assessment framework. On one side we introduce a protocol, namely the reprojection protocol, to take care of the spectral consistency issue. On the other side, a new index of the spatial consistency between the pansharpened image and the panchromatic band at full resolution is also proposed. Experimental results carried out on different datasets/sensors demonstrate the effectiveness of the proposed approach.
Submission history
From: Matteo Ciotola [view email][v1] Fri, 13 Aug 2021 09:35:45 UTC (817 KB)
[v2] Mon, 14 Mar 2022 08:51:45 UTC (21,107 KB)
[v3] Mon, 4 Apr 2022 12:43:36 UTC (24,602 KB)
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