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     Research Journal of Applied Sciences, Engineering and Technology


Comparison of Methods for IKONOS Images Pan-sharpening Using Synthetic Sensors

Oscar Rosario Belfiore, Claudio Meneghini, Claudio Parente and Raffaele Santamaria
Department of Sciences and Technologies, University of Naples
Research Journal of Applied Sciences, Engineering and Technology   2015  10:1084-1090
http://dx.doi.org/10.19026/rjaset.11.2123  |  © The Author(s) 2015
Received: June ‎17, ‎2015   |  Accepted: July ‎8, ‎2015  |  Published: December 05, 2015

Abstract

Many methods are present in literature for pan-sharpening of satellite images: they permit to transfer geometric resolution of panchromatic data to multispectral ones, but the results of their application are different. To evaluate the quality of these products, visual analysis is carried out, above all on the RGB composition to detect colour distortion. To quantize the level of similarity of the pan-sharpened images with them that should be achieved with effective more effective sensors, several indices are available such as: RMSE, correlation coefficients, UIQI, RASE. The principal limit of these indices consists in the terms of comparison because they compare the pan-sharpened images with the original ones that are with lower resolution. To supply the unavailability of the effective dataset with the same pixel dimensions of the pan-sharpened files, synthetic sensors can be introduced with lower resolution than the original ones. The correspondent degraded images can be submitted to pan-sharpening process and the results can be considered performed if similar to the original multispectral dataset. In this study IKONOS synthetic sensors are introduced to compare different methods: transforming the digital numbers into the radiance of the earth surface, original images of Campania Region are degraded and then submitted to some pan-sharpening approaches. The following methods are considered: multiplicative, simple mean, IHS, Fast IHS, Brovey, Weighted Brovey, Gram Schmidt, Zhang. Each resulting dataset is compared with the original multispectral one to evaluate the performance of each method.

Keywords:

At sensor radiance, data fusion, performance evaluation, remote sensing,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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