Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 863-869, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
13 Sep 2017
C. Pohl1, J. Moellmann2, and K. Fries3 1Institute of Computer Science, University of Osnabrueck, Germany
2imp GmbH, Wittekindstraße 100b, 44139 Dortmund, Germany
3ITS Service Group, Glückaufsegenstraße 61, 44265 Dortmund, Germany
Keywords: Image fusion, quality, standards, visual interpretation, quality indices, protocol Abstract. The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment) in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS) to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR) and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.
Conference paper (PDF, 9836 KB)

Citation: Pohl, C., Moellmann, J., and Fries, K.: STANDARDIZING QUALITY ASSESSMENT OF FUSED REMOTELY SENSED IMAGES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 863-869,, 2017.

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