Evaluating remote sensing image fusion algorithms for use in humanitarian crisis management

Chandi Witharana; Daniel L. Civco

doi:10.1117/12.973745

25 October 2012 Evaluating remote sensing image fusion algorithms for use in humanitarian crisis management

Chandi Witharana, Daniel L. Civco

Proceedings Volume 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III; 853807 (2012) https://doi.org/10.1117/12.973745
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

This study investigated how different fusion algorithms performed when applied to very high spatial resolution (VHSR) satellite images that encompass ongoing- and post-crisis scenes. The evaluation entailed twelve fusion algorithms. The selected algorithms were applied to GeoEye-1 satellite images taken over three different geographical settings representing natural and anthropogenic crises that had occurred in the recent past: earthquake-damaged sites in Haiti, flood-impacted sites in Pakistan, and armed-conflicted areas and internally displaced persons (IDP) camps in Sri Lanka. Spectral quality metrics included correlation coefficient, peak signal-to-noise ratio index, mean structural similarity index, spectral angle mapper, and relative dimensionless global error in synthesis. The spatial integrity of fused images was assessed using Canny edge correspondence and high-pass correlation coefficient. Under each metric, fusion methods were ranked and best competitors were identified. In this study, the Ehlers fusion, wavelet-PCA fusion (WVPCA), and the high-pass filter fusion algorithms reported the best values for the majority of spectral quality indices. Under spatial metrics, the University of New Brunswick and Gram-Schmidt fusion algorithms reported the optimum values. The color normalization sharpening and subtractive resolution merge algorithms exhibited the highest spectral distortions where as the WV-PCA algorithm showed the weakest spatial improvement. In conclusion, we recommend the University of New Brunswick algorithm if visual image interpretation is involved, whereas the high-pass filter fusion is recommended if semi- or fully-automated feature extraction is involved, for pansharpening VHSR satellite images of ongoing and post crisis sites

Citation Download Citation

Chandi Witharana and Daniel L. Civco "Evaluating remote sensing image fusion algorithms for use in humanitarian crisis management", Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 853807 (25 October 2012); https://doi.org/10.1117/12.973745

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