Markov random fields and graphs for uncertainty management and symbolic data fusion in an urban scene interpretation

Henri Moissinac; Henri Maitre; Isabelle Bloch

doi:10.1117/12.226846

17 November 1995 Markov random fields and graphs for uncertainty management and symbolic data fusion in an urban scene interpretation

Henri Moissinac, Henri Maitre, Isabelle Bloch

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Proceedings Volume 2579, Image and Signal Processing for Remote Sensing II; (1995) https://doi.org/10.1117/12.226846
Event: Satellite Remote Sensing II, 1995, Paris, France

Abstract

An image interpretation method is presented for the automatic processing of aerial pictures of a urban landscape. In order to improve the picture analysis, some a priori knowledge extracted from a geographic map is introduced. A coherent graph-based model of the city is built, starting with the road network. A global uncertainty management scheme has been designed in order to evaluate the final confidence we can have in the final results. This model and the uncertainty management tend to reflect the hierarchy of the available data and the interpretation levels. The symbolic relationships linking the different kinds of elements are taken into account while propagating and combining the confidence measures along the interpretation process.

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Henri Moissinac, Henri Maitre, and Isabelle Bloch "Markov random fields and graphs for uncertainty management and symbolic data fusion in an urban scene interpretation", Proc. SPIE 2579, Image and Signal Processing for Remote Sensing II, (17 November 1995); https://doi.org/10.1117/12.226846

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