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Benchmarking of Multispectral Pansharpening: Reproducibility, Assessment, and Meta-Analysis.

Luciano Alparone¹, Andrea Garzelli²

¹Department of Information Engineering, University of Florence, 50139 Florence, Italy.

Journal of Imaging

|January 24, 2025

Summary

Benchmarking pansharpening methods is challenging due to a lack of standardized assessment. This study proposes guidelines and an improved additive wavelet luminance proportional (AWLP) algorithm for reliable, reproducible evaluation of image fusion techniques.

Keywords:

benchmarking haze correction meta-analysis pansharpening remote sensing reproducibility

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Area of Science:

Remote Sensing
Image Processing
Computer Vision

Background:

Pansharpening enhances multiband image resolution using panchromatic data.
Evaluating pansharpening methods lacks standardization, hindering fair comparisons.
Proliferation of methods is hampered by inconsistent benchmarking.

Purpose of the Study:

To establish guidelines for reproducible and fair evaluation of pansharpening algorithms.
To introduce a novel benchmarking protocol for pansharpening methods.
To present an improved additive wavelet luminance proportional (AWLP) algorithm as an ideal benchmark.

Main Methods:

Developed guidelines for comparative evaluation using meta-analysis concepts.
Proposed an improved additive wavelet luminance proportional (AWLP) algorithm, termed AWLP-H, with haze correction.
Utilized a meta-analysis framework for cross-comparison of different pansharpening experiments.

Main Results:

The proposed AWLP-H algorithm exhibits performance, speed, and reproducibility.
The benchmarking protocol ensures automatic correction of atmospheric path radiance.
Assessment on five datasets confirmed reliable and consistent ranking of fusion methods.

Conclusions:

The developed guidelines and AWLP-H algorithm provide a standardized approach for pansharpening method evaluation.
Meta-analysis enhances the reliability of cross-experiment comparisons.
This work addresses the critical need for reproducible benchmarking in pansharpening research.