Local Registration and Deformation of a Road Cartographic Database on A SPOT Satellite Image

Herein, we propose a local registration method for cartographic road networks on SPOT satellite images based on Markov Random Fields (MRF) on graphs. Since the cartographic and image data are obtained from exogeneous sources, the noises degrading these data are of different nature. This phenomenon can create important differences between the data. In addition, cartographers sometimes introduce distortions, in the so-called generalization process, in the road map in order to emphasize some details of the road (like the bends of a mountain road). The proposed algorithm aims at correcting the error due to noise and generalization, hence increasing the accuracy of the road map. The proposed method consists in translating the cartographic data into a graph model, and then defining a MRF to fit the graph on the image

Local registration and deformation of a road cartographic database on A SPOT satellite image

Theme 3 - Interaction homme-machine, images, donnees, connaissances - Projet ArianaAvailable from INIST (FR), Document Supply Service, under shelf-number : 14802 E, issue : a.2000 n.3939 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas