The increasing availability of High Spatial Resolution (HSR) satellite images is an
opportunity to characterize and identify urban objects. Thus, the augmentation of the …

The multiplication of Very High Resolution (spatial or spectral) remote sensing images
appears to be an opportu-nity to identify objects in urban and periurban areas. The …

This paper deals with estimation of dense optical flow and ego-motion in a generalized
imaging system by exploiting probabilistic linear subspace constraints on the flow. We deal …

The multitude of satellite data products available offers a large choice for urban studies.
Urban space is known for its high heterogeneity in structure, shape and materials. To …

Remotely sensed images are more and more precise (spatial resolution under 1 meter). For
these images, objects of interest contains several pixels. Generally a segmentation method …

This paper deals with the description of the use of a collaborative multi-strategy classification
applied to image analysis. This system integrates different kinds of unsupervised …

This work presents an implementation of the fast Haar wavelet transform (FHWT)
mathematical algorithm assisted by the Mallat algorithm together with the ARSIS concept so …

In this chapter, the use of a collaborative multi-strategy clustering method, applied to image
analysis, is presented. This method integrates different kinds of clustering algorithms and …

The multiplication of High or Very High Resolution (spatial and spectral) remotely sensed
images is an opportunity to characterize and identify urban objects. Image analyses …

L'apprentissage d'algorithmes d'interprétation d'images est un processus complexe de
fouille de données. La méthode consistant à considérer les pixels de façon indépendante a …