Paper
4 December 1998 Extraction of geographic features using multioperator fusion
Pierre Dherete, Jacky Desachy
Author Affiliations +
Abstract
Automatic analysis of remote sensing images faces different problems: context diversity, complexity of information. To simplify identification and to limit the search space, we use extra data and knowledge to help the scene understanding. Diversity and imprecision of information sources generate new problems. The fuzzy logic theory is used to solve the problem of imprecision. Many extraction algorithms are used to provide a more reliable result. Extraction may be performed either globally on the whole image or locally using information of data bases. Each extractor produces a map of certainty factors for a given type of geographic features according to their characteristics: radiometry, color, linear, etc. Maps contain wrong detections due to imperfections of the detectors or non- completeness of generic models. So, we generate a new map using fusion to have a best credibility used to compute a dynamic programming. It finds an optimal path even if the linear feature is partially occluded. But the path is generally erratic due to noise. Then a snake-like technique smooth the path to clean the erratic parts and to tune the level of detail required to represent the geographic features on a map of a given scale. The result is used to update data bases.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pierre Dherete and Jacky Desachy "Extraction of geographic features using multioperator fusion", Proc. SPIE 3500, Image and Signal Processing for Remote Sensing IV, (4 December 1998); https://doi.org/10.1117/12.331887
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CITATIONS
Cited by 3 scholarly publications and 1 patent.
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KEYWORDS
Image fusion

Roads

Computer programming

Radiometry

Feature extraction

Fuzzy logic

Image processing

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