Alexandre Fournier

Former PhD Student, Supaéro / ENSAE

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Last publications in Ariana Research Group :

On the Illumination Invariance of the Level Lines under Directed Light: Application to Change Detection. P. Weiss and A. Fournier and L. Blanc-Féraud and G. Aubert. SIAM Journal on Imaging Sciences, 4(1): pages 448-471, March 2011. Keywords : Level Lines, topographic map, illumination invariance, Change detection, contrast equalization, remote sensing. @ARTICLE{SIIMS_2011, author = {Weiss, P. and Fournier, A. and Blanc-Féraud, L. and Aubert, G.}, title = {On the Illumination Invariance of the Level Lines under Directed Light: Application to Change Detection}, year = {2011}, month = {March}, journal = {SIAM Journal on Imaging Sciences}, volume = {4}, number = {1}, pages = {448-471}, url = {http://www.math.univ-toulouse.fr/~weiss/Publis/SIIMS_2011_Weiss.pdf}, pdf = {http://www.math.univ-toulouse.fr/~weiss/Publis/SIIMS_2011_Weiss.pdf}, keyword = {Level Lines, topographic map, illumination invariance, Change detection, contrast equalization, remote sensing} } Abstract : We analyze the illumination invariance of the level lines of an image. We show that if the scene surface has Lambertian reflectance and the light is directed, then a necessary and sufficient condition for the level lines to be illumination invariant is that the three-dimensional scene be developable and that its albedo satisfy some geometrical constraints. We then show that the level lines are “almost” invariant for piecewise developable surfaces. Such surfaces fit most of the urban structures. This allows us to devise a fast and simple algorithm that detects changes between pairs of remotely sensed images of urban areas, independently of the lighting conditions. We show the effectiveness of the algorithm both on synthetic OpenGL scenes and real QuickBird images. The synthetic results illustrate the theory developed in this paper. The two real QuickBird images show that the proposed change detection algorithm is discriminant. For easy scenes it achieves a rate of 85% detected changes for 10% false positives, while it reaches a rate of 75% detected changes for 25% false positives on demanding scenes. A contrast equalization procedure for change detection algorithms: applications to remotely sensed images of urban areas. A. Fournier and P. Weiss and L. Blanc-Féraud and G. Aubert. In International Conference on Pattern Recognition (ICPR), Tampa, USA, December 2008. Keywords : Change detection, Level Lines, remote sensing. Copyright : ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. @INPROCEEDINGS{l_lines_icpr08, author = {Fournier, A. and Weiss, P. and Blanc-Féraud, L. and Aubert, G.}, title = {A contrast equalization procedure for change detection algorithms: applications to remotely sensed images of urban areas}, year = {2008}, month = {December}, booktitle = {International Conference on Pattern Recognition (ICPR)}, address = {Tampa, USA}, url = {http://www.math.univ-toulouse.fr/~weiss/Publis/Conferences/icpr2008.pdf}, pdf = {http://www.math.univ-toulouse.fr/~weiss/Publis/Conferences/icpr2008.pdf}, keyword = {Change detection, Level Lines, remote sensing} } Détection et classification de changements sur des scènes urbaines en télédétection. A. Fournier. PhD Thesis, Institut Supérieur de l'Aéronautique et de l'Espace, October 2008. Keywords : détection de changements, Satellite images, lignes de niveau, Classification, Urban areas, statistiques directionnelles. @PHDTHESIS{Fournier08, author = {Fournier, A.}, title = {Détection et classification de changements sur des scènes urbaines en télédétection}, year = {2008}, month = {October}, school = {Institut Supérieur de l'Aéronautique et de l'Espace}, url = {http://tel.archives-ouvertes.fr/tel-00463593/fr/}, keyword = {détection de changements, Satellite images, lignes de niveau, Classification, Urban areas, statistiques directionnelles} } Résumé : Cette thèse aborde le problème de la détection de changements sur des images de scènes urbaines en télédétection. Les expériences ont été menées sur des couples d'images satellitaires panchromatiques haute résolution (< 1 m). À travers ce thème général, plusieurs problématiques, correspondant aux divers niveaux d'une chaîne de traitement, sont abordés, depuis la création d'un masque de changements jusqu'au raisonnement à un niveau objet. Dans ce manuscrit, nous abordons premièrement le problème de la détermination d'un masque de changements. Après avoir étudié les limites d'un algorithme de détection de changements, fondé sur l'analyse en composantes principales, nous proposons un algorithme tirant parti de l'invariance des lignes de niveau, fondé sur un modèle d'illumination et des hypothèses sur la régularité de la scène. Par la suite, nous abordons la classification des zones détectées comme changées au cours de l'étape précédente. D'abord, nous nous fondons uniquement sur les radiométries des couples de pixels. Enfin, nous étudions l'intérêt d'une composante géométrique dans la classification. Plus précisément, nous appliquons un algorithme d'approximation polygonale sur les zones connexes issues de la classification précédentes, puis nous classifions les formes obtenues compte tenu des orientations des côtés des polygones obtenus. Abstract : This thesis addresses the problem of change detection on remotely sensed urban scenes. experiences were run on couples of high resolution (<1m) panchromatic satellite images. Through this general theme, different problems, corresponding to different levels of a processing chain were addressed, from the determination of a change mask to an object level reasoning. In this work, we first address the problem of determining a change mask. We study the assets and limits of a change detection algorithm based on a Principal Component Analysis. We then propose a new algorithm that relies on the invariance of the level lines. It is based on a simple illumination model and some hypotheses on the scene regularity. Then we address the classification of the zones detected as changed during our first step. This is done by only considering the radiometries of each pixel couple. Finally, we study the interest of a geometric component in our classification. More precisely, we apply a polygonal approximation algorithm on the connected zones generated by the first classification, then we classify the obtained shapes according to the orientations of the polygon edges.

All publications in Ariana Research Group