Contribution au recalage d'images de modalités différentes à travers la mise en correspondance de nuages de points (Application à la télédétection)

L'utilisation d'images de modalités différentes est très répandue dans la résolution de problèmes liés aux applications de la télédétection. La raison principale est que chaque image d'une certaine modalité contient des informations spécifiques qui peuvent être intégrées en un modèle unique, afin d'améliorer notre connaissance à propos d'une scène spécifique. A cause du grand volume de données disponibles, ces intégrations doivent être réalisées de manière automatique. Cependant, un problème apparaît dès les premiers stades du processus : la recherche, dans des images de modalités différentes, de régions en correspondance. Ce problème est difficile à résoudre car la décision de regrouper des régions doit nécessairement reposer sur la part d'information commune aux images, même si les modalités sont différentes. Dans cette thèse, nous nous proposons donc d'apporter une contribution à la résolution de ce problèmeThe use of several images of various modalities has been proved to be quite useful for solving problems arising in many different applications of remote sensing. The main reason is that each image of a given modality conveys its own part of specific information, which can be integrated into a single model in order to improve our knowledge on a given area. With the large amount of available data, any task of integration must be performed automatically. At the very first stage of an automated integration process, a rather direct problem arises : given a region of interest within a first image, the question is to find out its equivalent within a second image acquired over the same scene but with a different modality. This problem is difficult because the decision to match two regions must rely on the common part of information supported by the two images, even if their modalities are quite different. This is the problem that we wish to address in this thesisAIX-MARSEILLE2-Bib.electronique (130559901) / SudocSudocFranceF

Contribution au recalage d'images de modalités différentes à travers la mise en correspondance de nuages de points : Application à la télédétection

L'utilisation d'images de modalités différentes est très répandue dans la résolution de problèmes liés aux applications de la télédétection. La raison principale est que chaque image d'une certaine modalité contient des informations spécifiques qui peuvent être intégrées en un modèle unique, afin d'améliorer notre connaissance à propos d'une scène spécifique. A cause du grand volume de données disponibles, ces intégrations doivent être réalisées de manière automatique. Cependant, un problème apparaît dès les premiers stades du processus : la recherche, dans des images de modalités différentes, de régions en correspondance. Ce problème est difficile à résoudre car la décision de regrouper des régions doit nécessairement reposer sur la part d'information commune aux images, même si les modalités sont différentes. Dans cette thèse, nous nous proposons donc d'apporter une contribution à la résolution de ce problèmeThe use of several images of various modalities has been proved to be quite useful for solving problems arising in many different applications of remote sensing. The main reason is that each image of a given modality conveys its own part of specific information, which can be integrated into a single model in order to improve our knowledge on a given area. With the large amount of available data, any task of integration must be performed automatically. At the very first stage of an automated integration process, a rather direct problem arises : given a region of interest within a first image, the question is to find out its equivalent within a second image acquired over the same scene but with a different modality. This problem is difficult because the decision to match two regions must rely on the common part of information supported by the two images, even if their modalities are quite different. This is the problem that we wish to address in this thesi

Procédé et système pour estimer une similarité entre deux images binaires

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A new geometric invariant to match regions within remote sensing images of different modalities

International audienceThe use of several images of various modalities has been proved to be useful for solving problems arising in many different applications of remote sensing. The main reason is that each image of a given modality conveys its own part of specific information, which can be integrated into a single model in order to improve our knowledge on a given area. With the large amount of available data, any task of integration must be performed automatically. At the very first stage of an automated integration process, a rather direct problem arises : given a region of interest within a first image, the question is to find out its equivalent within a second image acquired over the same scene but with a different modality. This problem is difficult because the decision to match two regions must rely on the common part of information supported by the two images, even if their modalities are quite different. In this paper, we propose a new method to address this problem

Pairing regions in remote sensing images of different modalities

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SAR image registration using a new approach based on the generalized hough transform

International audienceRadar Imaging using SAR systems provides specific information that is very useful in the frame of “Digital Earth ” applications (i.e. flood supervision, forestry or agriculture watch,). The main interest of such active systems is their capability to gather relevant data whatever the weather and the illumination conditions may be (cloudy, misty, during the night,). In addition, these systems give a useful “distance map ” thanks to the wave coherence. Most applications require a follow-up of the situation during weeks or months. Such a follow-up can only be performed if we are able to register images captured at different times. This registration problem is a very classical one and has been widely studied in Remote Sensing, but the proposed solutions are often dedicated to specific contexts (sensors, type of scenes, known relevant elements).Many algorithms have been proposed to register SAR images, and we give, in this paper, a global overview of these methods depending on the chosen approach. They may use filtering or not prior to registration, and they may use landmarks or not; but, in all cases, there will be to take into account the speckle that reduces the efficiency of classical methods for extracting features (e.g. landmarks,) to be paired in both images. During the last years (since 2000), a new set of methods, related to the Hough Transform concept, have been proposed: the algorithm we introduce in this communication can be considered as being in this class of approaches

A new approach for registering remote sensing images from various modalities

International audienceImage registration is a major issue in the field of Remote Sensing because it provides a support for integrating information from two or more images into a model that represents our knowledge on a given application. It may be used for comparing the content of two segmented images captured by the same sensor at different times; but it also may be used for extracting and assembling information from images captured by various sensors corresponding to different modalities (optical, radar,). The registration of images from different modalities is a very difficult problem because data representations are different (e.g. vectors for multispectral images and scalar values for radar ones) but also, and especially, because an important part of the information is different from an image to another (e.g. hyperspectral signature and radar response). And precisely, any registration process is based, explicitly or not, on matching the common information in the two images. The problem we are interested in is to develop a generic approach that enables the registration of two images from different modalities when their spatial representations are related by a rigid transformation. This situation often occurs, and it requires a very robust and accurate registration process to provide the spatial correspondence. First, we show that this registration problem between images from different modalities can be reduced to a matching problem between binary images. There are many approaches to tackle this problem, and we give an overview of these approaches. But we have to take into account the specificity of the context in which we have to solve this problem: we must select those points of both images that are associated with the same information, and not the other ones, in order to process the pairing that will lead to the registration parameters. The approach we propose is a Hough-like method that induces a separation between relevant and non-relevant pairings, the Hough space being a representation of the rigid transformation parameters. In order to characterize the relevant items in each image, we propose a new primitive that provides a local representation of patterns in binary images. We give a complete description of this approach and results concerning various types of images to register

Characterization of Similar Areas of Two 2D Point Clouds

International audienceWe here present a new approach to characterize similar areas of two 2D point clouds, which is a major issue in Pattern Recognition and Image Analysis. To do so, we define a similarity measure that takes into account several criteria such as invariance by rotation, outlier elimination, and one-dimensional structure enhancement. We use this similarity measure to associate locations from one cloud to the other, to use this result in the frame of a registration process between these two point clouds. Our main contributions are the integration of various one-dimensional structure representations into a unified formalism, and the design of a robust estimator to evaluate the common information related to these structures. Finally, we show how to use this approach to register images of different modalities

Mesure de similarité entre sous-parties de nuages de points 2D

International audienceCet article porte sur la caractérisation d'une mesure de similarité entre sous-parties de nuages de points 2D. Cette mesure est définie à partir d'une hypothèse généralement vérifiée sur des nuages de points issus de cas réels: ceux-ci possèdent des groupes de points qui s'organisent en structures linéiques, et qui apparaissent en même temps dans les différents nuages. Après avoir défini des primitives qui permettent une représentation unifiée de ces structures, nous montrons le lien qui existe entre la présence d'une information commune entre sous-nuages et la distribution des relations géométriques entre leurs primitives. Nous donnons alors une mesure de similarité invariante par rotation, ainsi qu'un algorithme permettant de la calculer

Earth observation using radar data: an overview of applications and challenges

International audienceAbstract The first pictures of the earth were taken from a balloon in the mid-19th century and thus started ‘earth observation’. Aerial missions in the 20th century enabled the build-up of outstanding photographic libraries and then with Landsat-1, the first civilian satellite launched in 1972, digital images of the earth became an operational reality. The main roles of earth observation have become scientific, economic and strategic, and the role of synthetic aperture radar (SAR) is significant in this overall framework. Radar image exploitation has matured and several operational programs regularly use SAR data for input and numerous applications are being further developed. The technological development of interferometry and polarimetry has helped further develop these radar based applications. This paper highlights this role through a description of actual applications and projects, and concludes with a discussion of some challenges for which SAR systems may provide significant assistance