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A Non-Bayesian Model for Tree Crown Extraction using Marked Point Processes
High resolution aerial and satellite images of forests have a key role to play in natural resource management. As they enable forestry managers to study forests at the... -
A marked point process of rectangles and segments for automatic analysis of D...
This work presents a framework for automatic feature extraction from images using stochastic geometry. Features in images are modeled as realizations of a spatial... -
Optimization Techniques for Energy Minimization Problem in a Marked Point Pro...
We use marked point processes to detect an unknown number of trees from high resolution aerial images. This approach turns to be an energy minimization problem, where... -
Hydrographic Network Extraction from Radar Satellite Images using a Hierarchi...
This report presents a two-step algorithm for unsupervised extraction of hydrographic networks from satellite images, that exploits the tree structures of such... -
A Polyline Process for Unsupervised Line Network Extraction in Remote Sensing
This report presents a new stochastic geometry model for unsupervised extraction of line networks (roads, rivers, etc.) from remotely sensed images. The line network... -
Point processes in forestry : an application to tree crown detection
In this research report, we aim at extracting tree crowns from remotely sensed images using marked point processes of discs and ellipses. Our approach is indeed to... -
Joint Bayesian decomposition of a spectroscopic signal sequence with RJMCMC
International audience -
Automatic building extraction from DEMs using an object approach and applicat...
International audience -
Building reconstruction from a single DEM
International audience -
LIDAR WAVEFORM MODELING USING A MARKED POINT PROCESS
International audience
