Image and data fusion emerged as a new research field in the late 1980s. In the following years, some aspects of image and data fusion have come to maturity. However, remotely sensed images and data in digital form with distinct spatial and spectral resolutions from different sources are steadily increasing, which requires combined spectral and spatial analyses, image/data fusion of features and models at different levels.
Image and data fusion aims at the integration of multi-sensor, multi-temporal, multi-resolution and multi-platform image data, together with geospatial data, GIS, in situ and other statistical data sets for improved information extraction, as well as to increase the reliability of the information. This leads to more accurate information that provides for robust operational performance, i.e. increased confidence, reduced ambiguity and improved classification enabling evidence-based management.
In recent years, new research areas in image and data fusion have been expanding, and many researchers are working for developing new image and data fusion methodologies, architectures and solutions. The International Journal of Image and Data Fusion (IJIDF) provides a single source of information for all aspects of image and data fusion methodologies, developments, techniques and applications. IJIDF focuses on the theory, methodology and applications of image and data fusion. Besides papers concerned with concept studies and methodology development of image and data fusion at different processing levels, articles on image and data fusion architectures, algorithms and novel applications are welcome. In addition, papers dealing with novel image and/or data fusion techniques, especially for new types of remote sensing sensors such as multi- and hyper-spectral satellite, airborne, terrestrial data including data from Sensor Webs and geo-statistical sources are specifically invited.
IJIDF publishes original research papers, occasional review papers, shorter letters and technical articles in all areas of image including data fusion, but not limited to the following aspects and topics: automatic registration/geometric aspects of fusing imagery from different sensors, with different spatial or spectral resolution; pixel, feature and decision level fusion algorithms and methodologies; data assimilation; multi-source classification and information extraction; integration of satellite, airborne and terrestrial sensor systems; fusing temporal data sets for change detection; data fusion applications in fields such as mapping, natural disaster monitoring, environmental security, etc.; image and data mining from multi-platform, multi-source, multi-scale, multi-temporal data sets.
In Vol. 1, No. 1 of IJIDF, eight high-quality papers have been accepted for publication. These papers cover several topics about image and data fusion, such as current status and trends of multi-source data fusion; the review of pixel-level fusion for pan sharpening; the concepts and practical aspects of classifier combination and score level fusion; the fusion of high resolution SAR and optical imagery for urban area land cover; the fusion of Radarsat-2 polarimetric images and the statistical method for the quality evaluation of image fusion. I hope it may help those who are interested in these topics.
After a year of preparation, IJIDF is now ready to launch. I would like to give a special thank to Professor J.L. van Genderen for his cooperation and encouragement in bringing this journal to fruition. At the same time, I would like to thank the authors and all members of the Editorial Board of IJIDF for their scientific contributions. We are looking forward to further progress in the research area of image and data fusion, as a continuation of the research reported in Vol. 1, No. 1.