Abstract

A correct assessment of pan-sharpened remote sensing imagery (fusion of panchromatic and multispectral im- ages) enables the improvement and ranking of pan sharpening algorithms. For this purpose, numerous quality indicators have been published in the literature; however, there is no consensus on their performance. In general, the pixel is used as a reference for the computation of these indicators and the result is a unique overall value that hardly represents the perceived quality by a human. In this paper, a supra-pixel approach to spatial quality assessment is addressed. Thus a methodology is proposed to exploit the differences among image objects (segments) to generate a spatial quality map. A database of eight fused images and their sources images has been created to test the proposed methodology. The pan- sharpening process was conducted using state of art fusion algorithms. Considering that usual approaches to quality assess- ment operate with a single scalar value, a score of the overall spatial quality is derived from this new measurement schema and compared it with other spatial quality measure, the frequency comparison index.