The e-shape project

International audienc

The ARSIS concept in image fusion: an answer to users needs

International audienceThe ARSIS concept (from its French name "amélioration de la résolution spatiale par injection de structures" that means improvement of the spatial resolution by structure injection) is briefly presented. It offers a framework for the synthesis of multi-modality images at highest spatial resolution by fusion of two sets of images. This concept is comprised of three types of models. These different types are introduced and a set of solutions for implementation proposed. Four solutions are detailed and applied to a satellite Ikonos image of the city of Hasselt, Belgium. The fusion products are analyzed visually and quantitatively. These analyses enhance the benefits of offering a set of solutions to remote sensing end-users in order to fulfill their needs

Data fusion of remotely sensed images using the wavelet transform : the ARSIS solution

ISSN 0277-786XInternational audienceEarth Observation satellites are often considered to deliver a high spatial resolution image and a set of high spectral resolution images with a lower spatial resolution. Users often want to take advantage of both the high spatial and high spectral resolutions. The ARSIS concept was specially designed to fulfill this requirement and to produce high spectral resolution images with the best spatial resolution available in the set of images with respect to the original spectral content. This concept is based on the wavelet transform and the multiresolution analysis. In this paper, the concept is presented and the different parameters are discussed. Examples of application of ARSIS to real case- studies are provided. Perspectives of use of such a concept are proposed and the benefits to user discussed

Comparison of different algorithms for the improvement of the spatial resolution of images

International audienceThis paper presents a comparison of the most frequently used methods for improving the spatial resolution of images. Several methods have been proposed for the merging of high spectral and high spatial resolution data in order to produce multispectral synthetic images having the highest spatial resolution available within the data set, and close to reality. The methods under consideration are Brovey transform, Intensity Hue Saturation (IHS), Principal Component Analysis (PCA), P+XS (from CNES) and four methods using the ARSIS concept, including the High-Pass Filtering (HPF). The duplication of pixels is also performed, in order to assess the benefits of fusion process. The present communication discusses the methods, their advantages and disadvantages

Urban street mapping using quickbird and Ikonos Images

International audienceThis article addresses the problem of urban street mapping from new high resolution satellite images. The proposed algorithm is divided in two sequential modules: a topologically correct graph of the street network is first extracted, and streets are then extracted as surface elements. The graph of the network is extracted by a following algorithm which minimizes a cost function. The surface extraction algorithm makes use of specific active contours (snakes) combined with a multiresolution analysis (MRA) for minimizing the problem of noise. This reconstruction phase is composed of two steps: the extraction of street segments and the extraction of street intersections. Results of the street network extraction are presented on Quickbird and Ikonos images. Future prospects are also expose

Fusion of high spatial and spectral resolution images: the ARSIS concept and its implementation

International audienceIn various applications of remote sensing, when high spatial resolution is required in addition with classification results, sensor fusion is a solution. From a set of images with different spatial and spectral resolutions, the aim is to synthesize images with the highest spatial resolution available in the set and with an appropriate spectral content. Several sensor fusion methods exist; most of them improve the spatial resolution but with a poor quality of the spectral content of the resulting image. Based on a multiresolution modeling of the information, the ARSIS concept (from its French name "Amélioration de la Résolution Spatiale par Injection de Structures") was designed in the aim of improving the spatial resolution together with a high-quality in the spectral content of the synthesized images. The general case of application of this concept is described. A quantitative comparison of all presented methods is achieved for a SPOT image. Another example of the fusion of SPOT XS (20 m) and KVR-1000 (2 m) images is given. Practical information for the implementation of the wavelet transform, the multiresolution analysis, and the ARSIS concept by practitioners is given with particular relevance to SPOT and Landsat imagery

Fusion d'images HRV de SPOT panchromatique et multibande à l'aide de la méthode ARSIS : apports à la cartographie urbaine

ISBN 2-920021-74-5International audienceL'objectif de cette communication est de présenter une nouvelle méthode permettant la production d'images à haute résolution spatiale, réunissant les qualités de la haute résolution spatiale et de la haute résolution spectrale des satellites d'observation de la Terre et plus particulièrement du capteur HRV de SPOT pour la cartographie urbaine. Les techniques de cartographie urbaine s'appuient sur des algorithmes de classification, dirigée ou non. La haute résolution spatiale ayant, pour cette application, un intérêt prépondérant, des méthodes permettant d'améliorer la résolution spatiale des images multibandes XS ont été développées. Une analyse de ces méthodes a montré qu'elles ne respectaient pas le contenu spectral original des images. La méthode ARSIS (amélioration de la résolution spectrale par injection de structures) a été développée pour fournir des images multibandes à haute résolution spatiale (dans ce cas 10 m). Elle permet la préservation de l'information originale de ces images et, par conséquent, d'améliorer l'efficacité des classificateurs. Elle s'appuie sur la transformée en ondelettes et l'analyse multirésolution, qui sont brièvement présentées. Une démonstration de cette méthode est présentée. Une évaluation quantitative a montré que la méthode ARSIS fournit de meilleurs résultats que les autres méthodes en termes de préservation de la qualité spectrale des images. Des classifications réalisées sur les données originales et sur les images résultant de la fusion sont comparées

Different implementations of the ARSIS concept to fulfill users needs

International audienceThere is a need for synthetic products that simulate satellite multispectral data at a higher spatial resolution. The users needs are various and somehow opposite: needs of high spatial resolution for accurate geometrical description of objects and needs for high spectral resolution for accurate spectral content and subsequent classification process. The ARSIS concept (from its French name "amélioration de la résolution spatiale par injection de structures" that means improvement of the spatial resolution by structure injection) permits to construct such synthetic products by fusion of two sets of data, namely panchromatic images at high spatial resolution and multispectral images at lower spatial resolution. It offers a framework wherein different models can be combined to form different solutions to better satisfy the users needs. An example is given of an Ikonos image of the city of Hasselt, Belgium

Benefits of fusion of high spatial and spectral resolutions images for urban mapping

International audienceThis communication presents a method allowing the combination of high spatial and spectral resolution images to improve the mapping of urban area. It makes use of two mathematical tools, the wavelet transform and the multiresolution analysis which are shortly introduced. This method, called ARSIS is then described. A qualitative comparison between a classical merging technique and the ARSIS method is presented through an example, the merging of SPOT XS images and the russian sensor KVR-1000. Then, the process used for urban mapping is explained and a map of a district in Riyadh, enhancing the roads and the buildings is presented

Data fusion for a better knowledge of urban areas

International audienceThis paper demonstrates the benefits of fused products for the analysis and mapping of urban areas. The fused products result from the synthesis of multispectral images at higher spatial resolution h, starting from a panchromatic image at resolution h and multispectral images at a lower resolution l. The application of the method ARSIS- RWM to the city of Marseille is discussed. It is further demonstrated that synthetic images may support further image processing dealing with the high frequencies