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Статті в журналах з теми "Images à résolution submétrique"
Ettinger, Susanne, Marie Zeghdoudi, Nélida Manrique Llerena, Anne-Françoise Yao-Lafourcade, and Jean-Claude Thouret. "L'apport de l'imagerie à haute résolution spatiale à la cartographie du risque de crue torrentielle." Revue Française de Photogrammétrie et de Télédétection, no. 209 (September 5, 2014): 73–79. http://dx.doi.org/10.52638/rfpt.2015.129.
Повний текст джерелаFeurer, Denis, Mohamed Amine El Maaoui, Mohamed Rached Boussema, and Olivier Planchon. "Méthode opérationnelle de production d'orthophotos et de MNT décimétriques à l'échelle du kilomètre carré par cerf-volant." Revue Française de Photogrammétrie et de Télédétection, no. 213 (April 26, 2017): 43–53. http://dx.doi.org/10.52638/rfpt.2017.190.
Повний текст джерелаBoussidi, Brahim, Ronan Fablet, Emmanuelle Autret, and Bertrand Chapron. "Accroissement stochastique de la résolution spatiale des traceurs géophysiques de l'océan: application aux observations satellitaires de la température de surface de l'océan." Revue Française de Photogrammétrie et de Télédétection, no. 202 (April 16, 2014): 66–78. http://dx.doi.org/10.52638/rfpt.2013.52.
Повний текст джерелаLéna, Pierre, and Guy Perrin. "Du flou des images astronomiques à un prix Nobel de physique." Reflets de la physique, no. 69 (June 2021): 21–27. http://dx.doi.org/10.1051/refdp/202169021.
Повний текст джерелаBarge, Olivier, and Emmanuelle Régagnon. "Vol au-dessus d'un tas de cailloux : l'usage en archéologie de photographies réalisées avec un cerf-volant." Revue Française de Photogrammétrie et de Télédétection, no. 213 (April 26, 2017): 95–104. http://dx.doi.org/10.52638/rfpt.2017.188.
Повний текст джерелаKasperski, Johan, and Marianne Chahine. "Apport des images satellitaires très haute résolution sur une étude de tracé d'infrastructure routière." Revue Française de Photogrammétrie et de Télédétection, no. 209 (January 11, 2015): 103–7. http://dx.doi.org/10.52638/rfpt.2015.100.
Повний текст джерелаHay, A., N. Rocher, G. Dethorey, G. Renard, and J. L. Bourges. "Le kératocône en images OCT haute résolution en domaine spectral." Journal Français d'Ophtalmologie 35, no. 8 (October 2012): 642–45. http://dx.doi.org/10.1016/j.jfo.2011.08.011.
Повний текст джерелаBarbey, Christelle, Jérôme Helbert, Arnaud Jaën, Elodie Pagot, Jean-Charles Samalens, Lilian Valette, Christian Germain, Dominique Guyon, and Jean-Pierre Wigneron. "Complémentarité des images Pléiades et drone pour la viticulture de précision dans le cadre du programme EarthLab." Revue Française de Photogrammétrie et de Télédétection, no. 208 (October 23, 2014): 123–29. http://dx.doi.org/10.52638/rfpt.2014.128.
Повний текст джерелаRegniers, Olivier, Lionel Bombrun, and Christian Germain. "Modélisation de texture basée sur les ondelettes pour la détection de parcelles viticoles à partir d'images Pléiades panchromatiques." Revue Française de Photogrammétrie et de Télédétection, no. 208 (September 8, 2014): 117–22. http://dx.doi.org/10.52638/rfpt.2014.122.
Повний текст джерелаDelvit, Jean-Marc, and Céline L'Helguen. "Observer la Terre en 3D avec Pléiades-HR." Revue Française de Photogrammétrie et de Télédétection, no. 209 (January 29, 2015): 11–16. http://dx.doi.org/10.52638/rfpt.2015.155.
Повний текст джерелаДисертації з теми "Images à résolution submétrique"
Li, Sizhuo. "Deep Learning for Forest Resource Mapping from Sub-Meter Resolution Imagery : Technical Insights and Methodologies." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASJ015.
Повний текст джерелаDeep learning has transformed numerous fields so far, propelled by improved algorithms and increased data accessibility. Remote sensing, in particular, offers significant opportunities for vision applications with direct socio-ecological implications. Forests represent a major environmental component, offering essential functions including climate regulation, biodiversity preservation, and interaction with living creatures. Departing from studies that reveal forest patterns using coarse resolution imagery or structural sensors like LiDAR, this thesis explores sub-meter resolution imagery - human-interpretable and highly detailed visual data covering the Earth. Forest attributes of different types are investigated, varying from tree characteristics to forest height and biomass. Technically, this thesis starts with a vanilla setup of in-domain semantic segmentation, delves into the regression of structural attributes, and ends with cross-domain adaptation. This brings insights into the learning capacity of vision models in the context of natural scene image understanding. The first part of the thesis introduces a deep learning framework to count, locate, and estimate the height of individual trees from aerial images at the national scale. An attention UNet is utilized to delineate individual tree crowns and count trees with point supervision. Tree height is estimated from optical imagery by learning a mapping from visual cues to canopy heights projected from LiDAR point clouds. Results are compared against field data to assess the practical values of the framework as supplementary data to support digitized national forest management. This study highlights the capacity of deep learning in characterizing visually interpretable forest and tree structures. Yet, challenges persist in learning more complex patterns from the optical data. This motivates the second study on forest biomass at stand level, a structural measure of forests typically collected on the ground. At larger scales, predominating methods apply statistical or machine learning models on multispectral imagery, often complemented by height data and calibrated with field data. To our knowledge, we are the first to demonstrate that stand-level biomass can be directly learned from sub-meter resolution RGB imagery, rich in forest and tree details, using convolutional neural networks and field data. This provides avenues for efficient and accurate quantification of forest biomass, a critical indicator of forest resources that supports nature preservation and carbon-neutral commitments. The first two studies employ deep learning systems to quantify forest attributes given a specific dataset, which follows the principal in-domain assumption of machine learning. Yet, degraded performance is often observed when applied to out-of-distribution data, a common scenario in practice. The third study aims to address the domain shift issue, exploring whether deep learning models trained on one dataset can be quickly adapted to new datasets with marginal efforts. We release a new dataset consisting of sub-meter resolution optical imagery collected in five countries and assess the cross-domain adaptability of various image-level regression tasks, including tree cover, total tree count, and average canopy height. By enforcing ordered embedding space during training, models are effectively prepared for later adaptation in source-free low-shot setups. Overall, this thesis introduces a collection of deep learning systems tailored for forest resource mapping with depth into technical and applied insights, contributing to sustainable management efforts for a greener future
Deep learning har hidtil transformeret talrige områder, drevet af forbedrede algoritmer og øgettilgængelighed af data. Fjernregistrering tilbyder betydelige muligheder for visionsapplikationermed direkte socioøkologiske implikationer. Skoveudgør en vigtig miljømæssig komponent og tilbyder essentielle funktioner, herunder klimaregulering, bevarelse af biodiversitet og interaktion medlevende væsener. Afgang fra studier, der afslørerskovmønstre ved hjælp af grovopløsningsbilledereller struktursensorer som LiDAR, udforsker denneafhandling sub-meteropløsningsbilleder - menneskefortolkelige og detaljerede visuelle data, derdækker Jorden. Forskellige skovattributter undersøges, lige fra trækarakteristika til skovhøjdeog biomasse. Teknisk set starter denne afhandling med en grundlæggende opsætning af semantisk segmentering inden for domænet, går videretil regression af strukturelle attributter og sluttermed tværfaglig tilpasning. Dette giver indsigt i visionmodellers indlæringskapacitet i konteksten afforståelse af naturscener. Afhandlingens førstedel introducerer et dybtlæringsrammeværk til attælle, lokalisere og estimere højden af individuelle træer fra luftfotos på nationalt plan. En opmærksomhed UNet bruges til at afgrænse individuelle trækroner og tælle træer med punktsupervision. Træhøjde estimeres fra optisk billedmaterialeved at lære en afbildning fra visuelle ledetråde tilkronhøjder projiceret fra LiDAR-punktskyer. Resultater sammenlignes med feltdatabaser for at vurdere rammeværkets praktiske værdier som supplement til understøttelse af digitaliseret nationalskovforvaltning. Denne undersøgelse fremhæverdybtlæringens evne til at karakterisere visuelt fortolkede skov- og træstrukturer. Dog vedvarerudfordringer i at lære mere komplekse mønstrefra det optiske data. Dette motiverer den anden undersøgelse af skovbiomasse på bestandsniveau, en strukturel måling af skove, der typiskindsamles på jorden. På større skalaer anvender dominerende metoder statistiske eller maskinlæringsmodeller på multispektralt billedmateriale,ofte suppleret med højdedata og kalibreret medfeltdatabaser. Efter vores viden er vi de førstetil at demonstrere, at bestandsniveauets biomassedirekte kan læres fra sub-meteropløsnings-RGBbilledmateriale, rigt på skov- og trædetaljer, vedhjælp af konvolutionelle neurale netværk og feltdatabaser. Dette giver muligheder for effektiv og præcis kvantificering af skovbiomasse, enkritisk indikator for skovressourcer, der støtternaturbevarelse og klimaneutrale forpligtelser. Deførste to studier benytter dybtlæringssystemer tilat kvantificere skovattributter ud fra et specifikt datasæt, hvilket følger den grundlæggendeantagelse om maskinlæring inden for domænet.Dog observeres der ofte nedsat præstation, nårdet anvendes på data uden for distributionen,en almindelig situation i praksis. Det tredjestudie sigter mod at adressere domæneskiftproblemet ved at undersøge, om dybtlæringsmodeller trænet på ét datasæt hurtigt kan tilpassestil nye datasæt med marginale bestræbelser.Vi frigiver et nyt datasæt bestående af submeteropløsnings optisk billedmateriale indsamleti fem lande og vurderer krydsdomænet tilpasningsevne for forskellige billedniveau-regressionstasks,herunder trædække, samlet trætælling og gennemsnitlig krones højde. Ved at håndhæve en ordnetindlejret rum under træning forberedes modellereffektivt til senere tilpasning i kildefrie lavskudsopsætninger. Overordnet introducerer denne afhandling en samling dybtlæringssystemer skræddersyet til kortlægning af skovressourcer med dybdei tekniske og anvendte indsigter, hvilket bidrager tilbæredygtige forvaltningsindsatser for en grønnerefremtid
Ploquin, Marie. "Super résolution pour l'amélioration de la résolution des images échographiques." Thesis, Tours, 2011. http://www.theses.fr/2011TOUR4025/document.
Повний текст джерелаMedical Imaging Ultrasound has several advantages such as its safety, ease of use, the diversity of organs that can be imaged and the low cost of this imaging mode. However, the images obtained by ultrasound suffer from relatively low resolution compared to others than can be obtain with an MRI or using X-rays. The major challenge of medical ultrasound is the ability to produce images with a resolution much finer, without modifying the nominal frequency.Work has been undertaken in this direction for some time. Several approaches have been explored. Most of the work done so far has been to work on the ultrasound acquiring device and particularly on ultrasonic probes, with main objective to increase the frequency of ultrasound used. This approach has led to the existence of high-resolution ultrasound, but with the reduction of the depth of exploration as an important limitation.Another approach is to treat numerically conventional ultrasound images to improve resolution. This method has several advantages, it allows to circumvent such difficulties caused by the reduction of depth of field due to the increase in the ultrasonic frequency.In this thesis, we present a method to improve the resolution of ultrasound images. The thesis to be to adapt this method to ultrasound imaging and to provide an estimate of the maximum theoretical resolution achieved by this method based on image parameters including SNR and the bandwidth of the PSF. We also proposed a method of superresolution suitable for ultrasound. By providing on improving theoretical superresolution and adaptation to the particular case of ultrasound, this thesis opens up on improving the resolution of ultrasound images by processing the signal and the image
Bouzkraoui, Mohammed. "Détection des arbres individuels dans des images de haute résolution." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0021/MQ47178.pdf.
Повний текст джерелаErus, Güray. "Reconnaissance d'objets cartographiques dans les images satellitaires à haute résolution." Paris 5, 2008. http://www.theses.fr/2008PA05S003.
Повний текст джерелаOur thesis' subject considers specifically the recognition of cartographic objects with a highly composite structure, such as roundabouts and bridges, on high resolution satellite images. Being man-made constructions, cartographic objects have regular geometrical features that distinguish them from other objects. We propose to exploit principally these features in order to obtain a representation of their inherent structure. A method to generate an explicit structural object model represented by Attributed Relational Graphs (ARGs) from images segmented by an expert is first developed. At the end of this preliminary stage we succeeded to generate object models for the roundabout and bridge categories. We then proposed to learn a more flexible model based on the appearances of the local parts of the objects using a statistical learning method. An implicit object model is learned by the fusion of weak classifiers obtained from geometrical primitives using the Adaboost algorithm. An object recognition method using an implicit model constructed by a parts and structures approach is then proposed. The model is learned using the Mean-Shift clustering algorithm. Finally, the methods are validated on satellite images provided by the CNES in the frame of a national competition and a cartographic application
Malek, Mohamed. "Extension de l'analyse multi-résolution aux images couleurs par transformées sur graphes." Thesis, Poitiers, 2015. http://www.theses.fr/2015POIT2304/document.
Повний текст джерелаIn our work, we studied the extension of the multi-resolution analysis for color images by using transforms on graphs. In this context, we deployed three different strategies of analysis. Our first approach consists of computing the graph of an image using the psychovisual information and analyzing it by using the spectral graph wavelet transform. We thus have defined a wavelet transform based on a graph with perceptual information by using the CIELab color distance. Results in image restoration highlight the interest of the appropriate use of color information. In the second strategy, we propose a novel recovery algorithm for image inpainting represented in the graph domain. Motivated by the efficiency of the wavelet regularization schemes and the success of the nonlocal means methods we construct an algorithm based on the recovery of information in the graph wavelet domain. At each step the damaged structure are estimated by computing the non local graph then we apply the graph wavelet regularization model using the SGWT coefficient. The results are very encouraging and highlight the use of the perceptual informations. In the last strategy, we propose a new approach of decomposition for signals defined on a complete graphs. This method is based on the exploitation of of the laplacian matrix proprieties of the complete graph. In the context of image processing, the use of the color distance is essential to identify the specificities of the color image. This approach opens new perspectives for an in-depth study of its behavior
Corpetti, Thomas. "Images & télédétection : analyse de séquences à basse et très haute résolution spatiale." Habilitation à diriger des recherches, Université Rennes 1, 2011. http://tel.archives-ouvertes.fr/tel-00616558.
Повний текст джерелаLehureau, Gabrielle. "Fusion de données optique et radar à haute résolution en milieu urbain." Paris, Télécom ParisTech, 2010. http://www.theses.fr/2010ENST0035.
Повний текст джерелаThe increasing quality of satellite images has generated interest in extracting man-made structures. Optical and radar sensors deliver images with unlike physical properties, thus it is interesting to fuse such images in order to benefit from joint observation. Such a process begins with registration of these images. We propose an automatic registration of radar and optical images without using sensors parameters. First, a rigid transformation is determined using a multi-scale pyramid of features representing the contours of roads and buildings. Secondly, a polynomial transformation is determined. The coefficients are obtained by associating points in both images using mutual information. We also developped a classification process in order to identify all scene objects. This method used both information from optical and radar images and svm classifier. We proved in this part a good robustness to segmentation and the interest of using both data to improve the classification, especially for roads and buildings. Finally we present an original method of fine registration for the buildings based on the assumption that “a trained classifier can recognize registrated buildings from unregistrated“. So, buildings are classified considering many translations in order to determine the good one. We also show the importance of contextual information to improve the fine registration, especially for buildings
Puissant, Anne. "INFORMATION GÉOGRAPHIQUE ET IMAGES A TRÈS HAUTE RÉSOLUTION UTILITÉ ET APPLICATIONS EN MILIEU URBAIN." Phd thesis, Université Louis Pasteur - Strasbourg I, 2003. http://tel.archives-ouvertes.fr/tel-00467474.
Повний текст джерелаSimonetto, Elisabeth. "Extraction 3-D de structures industrielles sur des images ramsès haute résolution par radargrammétrie." Rennes 1, 2002. https://tel.archives-ouvertes.fr/tel-00749513.
Повний текст джерелаMees, Wim. "Contribution à l'analyse distribuée de scènes : application aux images satellitaires multi spectrales, haute résolution." Nancy 1, 2000. http://www.theses.fr/2000NAN10282.
Повний текст джерелаКниги з теми "Images à résolution submétrique"
Katsaggelos, Aggelos Konstantinos. Super resolution of images and video. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2007.
Знайти повний текст джерелаEdition, Art. Cherche et Trouve: Trouve les Différences 4-8 Ans Livre de Jeux Cherche et Trouve les Différences de Noël Toutes les Images en Bonne Résolution 55 Dessins Pour Enfants, Fille et Garçon, de 4 à 8 Ans. Independently Published, 2020.
Знайти повний текст джерелаЧастини книг з теми "Images à résolution submétrique"
VERRIER, Nicolas, Matthieu DEBAILLEUL, Bertrand SIMON, and Olivier HAEBERLÉ. "Microscopie tomographique diffractive en transmission." In Imageries optiques non conventionnelles pour la biologie, 143–75. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9132.ch5.
Повний текст джерелаGARZELLI, Andrea, and Claudia ZOPPETTI. "Analyse multitemporelle d’images Sentinel-1/2 pour le suivi de l’utilisation des sols." In Détection de changements et analyse des séries temporelles d’images 1, 221–45. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9056.ch8.
Повний текст джерелаFredj, A. Ben, and G. Nihottl. "Observation en microscopie électronique à haute résolution d'oxydes à grande maille (c-Dy203) et interprétation des images obtenues." In October 16, 351. De Gruyter, 1985. http://dx.doi.org/10.1515/9783112500941-005.
Повний текст джерелаТези доповідей конференцій з теми "Images à résolution submétrique"
Magri, Julie, Ludovic Grossard, Laurent Delage, and François Reynaud. "Projet ALOHA : Interféromètre fibré à conversion de fréquence dans le moyen et lointain infrarouge." In Les journées de l'interdisciplinarité 2022. Limoges: Université de Limoges, 2022. http://dx.doi.org/10.25965/lji.83.
Повний текст джерелаFERRANDON, Erwan, Mathis COURANT, Camélia POPESCU, Yann LAUNAY, Sophie ALAIN, and Claire LEFORT. "Un pipeline instrumental et computationnel pour visualiser des particules virales de SARS-CoV-2 en suspension." In Les journées de l'interdisciplinarité 2022. Limoges: Université de Limoges, 2022. http://dx.doi.org/10.25965/lji.684.
Повний текст джерелаЗвіти організацій з теми "Images à résolution submétrique"
Dietiker, B., A. J. M. Pugin, H. L. Crow, K. D. Brewer, and H. A. J. Russell. Seismic survey results from a buried valley study, Elora and Guelph, Ontario. Natural Resources Canada/CMSS/Information Management, 2024. http://dx.doi.org/10.4095/pd24sxky79.
Повний текст джерела