Development of a standardized method for visual quality assessment of image fusion results
Realized for the purpose of my Master Thesis in the context of Geoinformatics by Kevin Fries (Supervisor: Christine Pohl,
The amount of different remote sensing imagery has grown drastically in recent years. There is a wide variety of data having different advantages and disadvantages apart from their physical limitations. The approach of image fusion can be applied in this context because two or more images can be combined to obtain a new one that contains benefits from the used images.

In this regard, many techniques have evolved within last years which allow the fusion of image data. Many different methods have been developed to evaluate the quality of the results to allow such an evaluation. Most of these so called quantitative methods rely on a statistical background.

On the other hand it is possible to evaluate an image qualitatively, i.e. visually and mostly subjective. This method is intuitive and has the advantage that human perception can recognize aspects that may not be expressed by an algorithm. The visual assessment of image quality lacks a standardized method.
Purpose of this study
By the help of this study a protocol is developed. It should enable and standardize a method to visually assess the quality of a fused image based on specific aspects. With this it shall be possible to evaluate different fused images visually and objectively. The protocol is intended to target different application fields and therefore can be used universally.
Any data collected in this study will be kept private and will not be given to third parties. Published results will not contain names or institutions. Therefore it will not be possible to identify the participants afterwards.

Participation in this study is voluntary. By participating, you agree that the data collected (except the personal information) can be used in publications.
If you subsequently have any questions about this study, you can contact me using the following email adress:

Kevin Fries

Osnabrueck University
Institute of Computer Science
Wachsbleiche 27
49090 Osnabrueck
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