Mihai Datcu, Klaus Seidel
The advent of meter resolution Synthetic Aperture Radar SAR images is a double explosion regarding the data volume and its information content. Compared with the SAR images at tens of meter resolution, the meter resolution images are increasing the data volume, and the diversity of land cover or man-made structures and objects which can be extracted with higher details up to 2 or 3 orders of magnitude. Thus the use of single SAR images is fantastically growing, and incredibly enlarging the areas of applications.
High-resolution imaging is a persistent goal for many users of SAR remote sensing data as it allows better detection, discrimination and classification of the objects contained within a recorded scene. High resolution can be obtained either by instrument design, by data acquisition methods, or by dedicated post processing and interpretation of the acquired data. We will compare various methods used for SAR instruments and their interpretation processing chains. Primary criteria for high resolution imaging as encountered in remote sensing of solid surfaces and ATR are ground resolution per pixel, image formation models, attainable contrast and signal-to-noise ratio, removal of instrumental and non-target effects, geometrical correction, use of multi-channel and neighborhood target property data like spectral and textural signatures, and the potential for data fusion from multiple sources.
Mihai Datcu received the M.S. and Ph.D. degrees in Electronics and Telecommunications from the University “Politechnica” of Bucharest UPB, Romania, in 1978 and 1986. In 1999 he received the title “Habilitation à diriger des recherches” from Université Louis Pasteur, Strasbourg, France. He holds a professorship in electronics and telecommunications with UPB since 1981. Since 1993 he is scientist with the German Aerospace Center (DLR), Oberpfaffenhofen. He is developing algorithms for model based information retrieval from high complexity signals and methods for scene understanding from synthetic aperture radar (SAR) and interferometric SAR data. He is engaged in research related to information theoretical aspects and semantic representations in advanced communication systems. Currently he is Senior Scientist and Image Analysis research group leader with the Remote Sensing Technology Institute (IMF) of DLR, Oberpfaffenhofen, coordinator of the CNES-DLR-Telecom ParisTech Competence Centre on Information Extraction and Image Understanding for Earth Observation, and professor at Paris Institute of Technology - Telecom ParisTech.
Klaus Seidel received his B.S. degree in experimental physics in 1965 and the PhD degree in 1971, both from the Swiss Federal Institute of Technology (ETHZ). He was with the Computer Vision Lab at ETHZ and head of the remote sensing group until 2002. Since 1987 he was a Swiss Delegate and Expert in various ESA Working Groups and at the same time functioning as the National Point of Contact for Switzerland for Earth Observation data. He is currently consultant for ESA projects specialized in image information mining related to remote sensing archives. He was also teaching courses in digital processing of satellite images and has published several papers concerning snow cover monitoring, geometric correction and multispectral analysis of satellite images, and on remote sensing image archival. In 2003 he published together with J. Martinec a book on “Remote Sensing in Snow Hydrology”. He was involved in the Knowledge-driven Image Information Mining (KIM) project and is contributing to the Knowledge Enabled Services KES, KIM Validation and Knowledge Centered EO (KEO) projects for ESA.
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