Marc Walessa

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Automatic interpretation of remote-sensing (RS) images and the growing interest for query by image content from large remote-sensing image archives rely on the ability and robustness of information extraction from observed data. In Parts I and II of this article, we turn the attention to the modern Bayesian way of thinking and introduce a pragmatic approach(More)
In this paper, we present Gibbs random field models in the form of a powerful toolbox for spatial information extraction from remote sensing images. These models are defined via parametrised energy functions that characterise local interactions between neighbouring pixels. After shortly revisiting the information theoretical concept and defining a family of(More)
The objective of the proposed algorithm is to identify unobstructed space in front of a moving passenger car by means of a single monochrome camera. The approach is divided into two principal parts. First a model based road border recognition with focus on a sophisticated image feature extraction was developed to deal with different sources of distracting(More)
1 The new generation of high resolution imaging satellites acquires huge amounts of data which are stored in large archives. The state-of-the-art systems for data access allow only queries by geographical location, time of acquisition or type of sensor. This information is often less important than the content of the scene, i.e. structures, objects or(More)
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