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Shadow detection and removal in RGB VHR images for land use unsupervised classification / A. Movia in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
Titre : Shadow detection and removal in RGB VHR images for land use unsupervised classification Type de document : Article/Communication Auteurs : A. Movia, Auteur ; A. Beina, Auteur ; F. Crosilla, Auteur Année de publication : 2016 Article en page(s) : pp 485 - 495 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse d'image numérique
[Termes IGN] analyse procustéenne
[Termes IGN] anisotropie
[Termes IGN] classification non dirigée
[Termes IGN] détection d'ombre
[Termes IGN] détection de changement
[Termes IGN] factorisation de Cholesky
[Termes IGN] image à très haute résolution
[Termes IGN] image RVBRésumé : (Auteur) Nowadays, high resolution aerial images are widely available thanks to the diffusion of advanced technologies such as UAVs (Unmanned Aerial Vehicles) and new satellite missions. Although these developments offer new opportunities for accurate land use analysis and change detection, cloud and terrain shadows actually limit benefits and possibilities of modern sensors.
Focusing on the problem of shadow detection and removal in VHR color images, the paper proposes new solutions and analyses how they can enhance common unsupervised classification procedures for identifying land use classes related to the CO2 absorption.
To this aim, an improved fully automatic procedure has been developed for detecting image shadows using exclusively RGB color information, and avoiding user interaction. Results show a significant accuracy enhancement with respect to similar methods using RGB based indexes.
Furthermore, novel solutions derived from Procrustes analysis have been applied to remove shadows and restore brightness in the images. In particular, two methods implementing the so called “anisotropic Procrustes” and the “not-centered oblique Procrustes” algorithms have been developed and compared with the linear correlation correction method based on the Cholesky decomposition.
To assess how shadow removal can enhance unsupervised classifications, results obtained with classical methods such as k-means, maximum likelihood, and self-organizing maps, have been compared to each other and with a supervised clustering procedure.Numéro de notice : A2016-793 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.05.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82510
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 485 - 495[article]
Titre : Géomatique, modèles numériques de terrain : mathématiques appliquées à la modélisation du relief Type de document : Guide/Manuel Auteurs : Patrick Julien Editeur : Paris : Ellipses-Edition Marketing Année de publication : 2016 Collection : Technosup Sous-collection : Niveau C - Compléments (approfondissement, spécialisation) Importance : 276 p. Format : 17 x 26 cm ISBN/ISSN/EAN : 978-2-340-01178-6 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algèbre linéaire
[Termes IGN] calcul matriciel
[Termes IGN] diagramme de Voronoï
[Termes IGN] krigeage
[Termes IGN] modèle numérique de terrain
[Termes IGN] système linéaire
[Termes IGN] triangulation de DelaunayIndex. décimale : 33.60 Applications photogrammétriques - usage combiné de la photogrammétrie et de la lasergrammétrie Résumé : (Editeur) L’ouvrage décrit en détail quelques méthodes mathématiques de construction de modèles numériques de terrain (MNT) sous forme de surfaces, à partir de données non structurées (échantillon irrégulier de points) ou difficiles à utiliser directement en ordinateur (courbes de niveau). Les surfaces construites peuvent s’appuyer sur un maillage (carré régulier ou triangulaire irrégulier), ou être représentées par une expression mathématique sans maillage sous-jacent, comme les surfaces splines « plaque mince » et les surfaces à fonction de base radiale (ou surfaces de « krigeage »). Ainsi représenté par une surface mathématique, le MNT peut être facilement exploité en ordinateur. Après un aperçu global des MNT et de leurs utilisations, le livre expose les méthodes de construction proprement dites, sans donner toutes les justifications des propriétés mathématiques énoncées ou utilisées. Ces justifications, avec les définitions nécessaires, font l’objet des derniers chapitres, de sorte que l’ensemble constitue un ouvrage autonome comportant des démonstrations complètes. Le livre s’adresse aux étudiants, ingénieurs, chercheurs ou développeurs et utilisateurs de systèmes d’information concernés par les aspects mathématiques des MNT. Il peut aussi intéresser les lecteurs curieux de découvrir des exemples d’applications des mathématiques. Note de contenu : 1. Aperçu sur les modèles numériques de terrain
2. Surfaces H(x,y) représentant un MNT
3. Ajustement d’une surface sur un échantillon de points (ou structuration du MNT)
4. Compléments de calcul matriciel et algèbre linéaire
5. Résolution numérique d’un système linéaire
6. Projection sur l’ellipsoïde, calcul de la latitude
7. Courbure des courbes et surfaces
8. Résultats auxiliaires pour les surfaces splines plaque mince
9. Probabilités pour le krigeage
10. Polygones convexes, diagramme de Voronoï, triangulation de DelaunayNuméro de notice : 22504 Affiliation des auteurs : non IGN Thématique : IMAGERIE/MATHEMATIQUE Nature : Manuel de cours Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80982 Réservation
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Titre : Regional gravity field modelling with radial basis functions Type de document : Thèse/HDR Auteurs : Tobias Wittwer, Auteur Editeur : Delft : Netherlands Geodetic Commission NGC Année de publication : 2009 Collection : Netherlands Geodetic Commission Publications on Geodesy, ISSN 0165-1706 num. 72 Importance : 190 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-90-6132-315-0 Note générale : Bibliographie
Document téléchargeable sur le site de NCG : voir lien dans la noticeLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] Antarctique
[Termes IGN] Canada
[Termes IGN] champ de pesanteur local
[Termes IGN] données GOCE
[Termes IGN] données GRACE
[Termes IGN] factorisation de Cholesky
[Termes IGN] filtre de Wiener
[Termes IGN] fonction de base radiale
[Termes IGN] Groenland
[Termes IGN] harmonique sphérique
[Termes IGN] levé gravimétrique
[Termes IGN] modèle de géopotentiel
[Termes IGN] modèle mathématiqueRésumé : (Auteur) Terrestrial gravimetry, airborne gravimetry, and the recent dedicated satellite gravity missions Challenging Minisatellite Payload (CHAMP), Gravity Recovery and Climate Experiment (GRACE), and Gravity and Ocean Circulation Explorer (GOCE) provide us with high-quality, high-resolution gravity data, which are used in many application areas such as
1. the computation of global static gravity fields, in support of precise orbit determination of many Earth observation satellites;
2. the quantification and interpretation of mass transport in the Earth system such as the shrinking of ice sheets, the shifting of ocean currents, and water storage variations;
3. the computation of high resolution regional and local gravity fields in support of height system realisation and the modelling of reservoirs and geophysical features.
Traditionally, for each data set (satellite, airborne, terrestrial) dedicated data processing schemes have been developed using different estimation principles, parametrisations, etc. The optimal combination of different data sets would benefit of a methodology that can be used for any type of data. Elements of this methodology comprise a uniform parametrisation, estimation principle, data weighting scheme, regularisation, and error propagation.
In the framework of this thesis, such a methodology is developed. It uses radial basis functions (RBFs) as parametrisation. They have parameters that allow us to tune their approximation properties as function of the data coverage and distribution and the signal variations. This makes them equally well suited for global and local parametrisation. Moreover, there exists an analytical relationship between a spherical harmonic representation and a radial basis function representation, which allows the latter to be transformed into the former, without any approximation error. Among others, this has the advantage that one can make use of existing processing tools, such as spectral analysis.
Although radial basis functions are not new in gravity field modelling, there are many important issues which have not yet been addressed or require further research. The main research question underlying this thesis is: "Are radial basis functions a suitable parametrisation for global and regional models of the mean and time-variable gravity field, and if so, how do they perform compared with spherical harmonic solutions?" Directly related to this is the question: "Are there situations where radial basis functions models outperform spherical harmonic solutions?" The answer to both questions is positive as will be shown in this thesis.
There are two important aspects that determine the quality of a gravity field model based on radial basis functions: 1) the spatial distribution of the radial basis functions, i.e. the basis function network design, and 2) the choice of the bandwidths of the radial basis functions. For both problems, semi-automatic algorithms have been developed. Data-adaptive network design and local refinement avoid respectively over- and under-parametrisation by fine-tuning the basis function network based on the data. The basis function bandwidth is determined by optimising the fit to the data including control data.
The computation of regional gravity fields constitutes a considerable numerical workload, especially since the methodology presented here does not use an iterative normal equation solver (e.g., the preconditioned conjugate gradient method). Instead, a Cholesky solver is used, which requires the assembly of the complete normal equation system. For this purpose the program is numerically optimised and fully parallelised for hybrid high performance computer architectures. This guarantees optimal performance on all types of parallel computers and handles the memory requirements.
The modelling of satellite data with radial basis functions is investigated using real data of the GRACE satellites collected over the period 2003-2006. An optimal Wiener filter has been developed for radial basis functions in line with the optimal Wiener filter approach previously developed at DEOS for spherical harmonic representations. Monthly GRACE gravity models computed using radial basis function are compared to spherical harmonic models, and validated using independent data provided by the Ice Cloud and Land Elevation Satellite (ICESat), radar altimetry satellites, and the global hydrological model PCR-GLOBWB. Two applications were considered: 1) mass variations over Greenland and Antarctica and 2) water storage variations in river basins. The results show that the radial basis function approach yields solutions that are of at least the same quality as global models using spherical harmonics. There is evidence that radial basis functions may provide better spatial resolution and more realistic amplitudes in particular in high-latitude areas. For instance, it will be shown that radial basis function solutions detected signal that could not be seen in spherical harmonic solutions.
Two test areas are used for regional gravity field modelling using real terrestrial data: An area in the northeastern USA and a larger area in eastern Canada. The results show that the data-adaptivity and local refinement algorithms developed in the framework of this thesis provide good solutions of constant quality regardless of the initially chosen grid spacing. The models are compared to the official regional geoid models GEOID03 and CGG05, respectively. In both cases, rms errors of several centimetres remain, which are attributed to different input data and processing strategies.
The combination of satellite and terrestrial data is tested using simulated global and regional data sets. It is shown that a joint inversion of the two data sets yields combined solutions which are significantly better than a solution using the traditional remove-restore approach. The addition of satellite data with the corresponding stochastic model compensates the reduced quality of the terrestrial data at long wavelengths.
The examples show that the regional modelling methodology presented here is a very flexible approach that can be applied to all types of gravity data and data distributions, regardless of application, data source, and area size. The quality of the solutions is at least equal to the solutions developed for the stand-alone inversion of individual data sets, while radial basis functions offer numerical benefits. As a result, this approach is already used for marine geoid modelling, and recommended for the modelling of airborne gravity data and data of the GOCE satellite, and for the joint inversion of satellite, airborne and ground-based gravity data.Note de contenu : Nomenclature
1 Introduction
1.1 Background
1.2 Motivation
1.2.1 Regional modelling from satellite data
1.2.2 Regional modelling from terrestrial data
1.2.3 Combined modelling of satellite and terrestrial data
1.2.4 Radial basis functions
1.3 Prior research on radial basis functions
1.4 Research objectives
1.5 Outline of thesis
2 Radial basis functions
2.1 Gravity field representations
2.1.1 Spherical harmonics
2.1.2 Radial basis functions
2.2 RBF types and behaviour in the spectral domain
2.3 Behaviour in the spatial domain
2.4 Relation of RBFs to a spherical harmonic representation
2.5 Choice of RBF characteristics
2.5.1 Choice of the kernel
2.5.2 Bandwidth selection
2.6 RBF network design
2.6.1 Grids
2.6.2 Adaptation to data
2.6.3 Local refinement
2.7 Multi-scale modelling
2.7.1 Introduction
2.7.2 Methodology
2.7.3 Filtering
3 Mathematical model and estimation principle
3.1 Functional model
3.2 Stochastic model
3.3 Least-squares estimation and regularisation
3.4 Solution strategies
3.4.1 Cholesky factorisation
3.4.2 Conjugate gradients
3.5 Variance component estimation .
3.5.1 Normal equations
3.5.2 Variance component estimation
3.5.3 Stochastic trace estimation
4 Numerical aspects
4.1 Numerical optimisation
4.1.1 Constant expressions in "do"-loops
4.1.2 Computation of the design matrix
4.1.3 Normalisation of coordinates
4.1.4 Normalisation of basis functions
4.2 Fast synthesis
4.3 Parallelisation
4.3.1 Problem description
4.3.2 Parallel computer architectures .
4.3.3 Parallelisation for shared memory computers
4.3.4 Parallelisation for distributed memory computers
4.3.5 Hybrid parallelisation
4.3.6 Results of parallelisation
4.4 Summary and conclusions
5 Gravity field modelling from satellite data
5.1 Functional model
5.1.1 Three-point range combination approach
5.1.2 Residual accelerations
5.1.3 Equivalent water heights
5.1.4 Trend and signal amplitude estimation
5.2 Stochastic model
5.3 Optimal filtering
5.3.1 Introduction
5.3.2 Signal covariance matrix computation
5.3.3 Noise level estimation
5.4 RBF network design
5.4.1 Grid choice
5.4.2 Data-adaptivity and local refinement
5.4.3 Parametrised area
5.5 Bandwidth selection
5.6 Results.
5.6.1 Comparison of unfiltered RBF and spherical harmonic solution
5.6.2 Models used for comparison
5.6.3 Recovery of ice mass loss in Greenland and Antarctica
5.6.4 Recovery of terrestrial water storage variations
5.7 Summary and conclusions
6 Local gravity field modelling from terrestrial data
6.1 Functional model
6.1.1 Functional model for gravity disturbances
6.1.2 Functional model for gravity anomalies
6.1.3 Functional model for height anomalies
6.2 RBF network design
6.2.1 Grid choice
6.2.2 Data-adaptivity and local refinement
6.2.3 Parametrised area
6.3 Bandwidth selection
6.4 Results
6.4.1 Northeastern USA
6.4.2 Canada
6.5 Summary and conclusions
7 Combined modelling of satellite and terrestrial data
7.1 Combination strategies
7.1.1 Remove-restore approach
7.1.2 High-pass filtering
7.1.3 Direct combination
7.1.4 Combination with satellite-only solution
7.2 RBF network design and bandwidth selection
7.3 Results
7.3.1 Global test
7.3.2 Regional test
7.4 Summary and conclusions
8 Summary, conclusions and recommendations
8.1 Summary and conclusions
8.2 Recommendations for further researchNuméro de notice : 15511 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère Note de thèse : PhD thesis En ligne : https://www.ncgeo.nl/index.php/en/publicatiesgb/publications-on-geodesy/item/258 [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=62744 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 15511-01 30.42 Livre Centre de documentation Géodésie Disponible
Titre : A new method for three-carrier GNSS ambiguity resolution Type de document : Article/Communication Auteurs : U. Fernandez-Plazaola, Auteur ; T. Martin-Guerrero, Auteur ; J. Entrambasaguas, Auteur Année de publication : 2008 Article en page(s) : pp 269 - 278 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] factorisation de Cholesky
[Termes IGN] phase GPS
[Termes IGN] résolution d'ambiguïté
[Termes IGN] signal GNSSRésumé : (Auteur) A new method for resolving the carrier-phase integer ambiguity in Global Navigation Satellite Systems (GNSS) is presented: the MOdified Cholesky factorization for Ambiguity (MOCA) resolution. The characteristics and features of this method are described and results obtained using a software simulator and an emulator are presented to validate its efficiency. The results are then compared to those obtained using another existing method and good performance of the MOCA method in new GNSS systems is shown. Furthermore, the proposed method yields accurate results even when short time spans are used or when there are poor estimations of measurement error, making it immune to non-ideal conditions and ultimately a practical solution for real applications. Copyright Springer Numéro de notice : A2008-170 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29165
in Journal of geodesy > vol 82 n° 4-5 (April - May 2008) . - pp 269 - 278[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 266-08042 RAB Revue Centre de documentation En réserve 3L Disponible 266-08041 RAB Revue Centre de documentation En réserve 3L Disponible
Titre : Kalman filtering, theory and practice using MATLAB, [Third edition] Type de document : Monographie Auteurs : Mohinder S. Grewal, Auteur ; Angus P. Andrews, Auteur Mention d'édition : 3 Editeur : New York, Londres, Hoboken (New Jersey), ... : John Wiley & Sons Année de publication : 2008 Importance : 575 p. Format : 16 x 24 cm + cédérom ISBN/ISSN/EAN : 978-0-470-17366-4 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] filtrage linéaire
[Termes IGN] filtrage non linéaire
[Termes IGN] filtre de Kalman
[Termes IGN] GPS-INS
[Termes IGN] Matlab
[Termes IGN] positionnement par GNSS
[Termes IGN] programmation stochastique
[Termes IGN] système linéaireRésumé : (Editeur) This book provides readers with a solid introduction to the theoretical and practical aspects of Kalman filtering. It has been updated with the latest developments in the implementation and application of Kalman filtering, including adaptations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation. All software is provided in MATLAB, giving readers the opportunity to discover how the Kalman filter works in action and to consider the practical arithmetic needed to preserve the accuracy of results. Note de contenu : 1. General Information
1.1 On Kalman Filtering
1.2 On Optimal Estimation Methods
1.3 On the Notation Used In This Book
1.4 Summary
Problems
2. Linear Dynamic Systems
2.1 Chapter Focus
2.2 Dynamic System Models
2.3 Continuous Linear Systems and Their Solutions
2.4 Discrete Linear Systems and Their Solutions
2.5 Observability of Linear Dynamic System Models
2.6 Summary
Problems
3. Random Processes and Stochastic Systems
3.1 Chapter Focus
3.2 Probability and Random Variables (RVs)
3.3 Statistical Properties of RVs
3.4 Statistical Properties of Random Processes (RPs)
3.5 Linear RP Models
3.6 Shaping Filters and State Augmentation
3.7 Mean and Covariance Propagation
3.8 Relationships Between Model Parameters
3.9 Orthogonality Principle
3.10 Summary
Problems
4. Linear Optimal Filters and Predictors
4.1 Chapter Focus
4.2 Kalman Filter
4.3 Kalman–Bucy Filter
4.4 Optimal Linear Predictors
4.5 Correlated Noise Sources
4.6 Relationships Between Kalman–Bucy and Wiener Filters
4.7 Quadratic Loss Functions
4.8 Matrix Riccati Differential Equation
4.9 Matrix Riccati Equation In Discrete Time
4.10 Model Equations for Transformed State Variables
4.11 Application of Kalman Filters
4.12 Summary
Problems
5. Optimal Smoothers
5.1 Chapter Focus
5.2 Fixed-Interval Smoothing
5.3 Fixed-Lag Smoothing
5.4 Fixed-Point Smoothing
5.5 Summary
Problems
6. Implementation Methods
6.1 Chapter Focus
6.2 Computer Roundoff
6.3 Effects of Roundoff Errors on Kalman Filters
6.4 Factorization Methods for Square-Root Filtering
6.5 Square-Root and UD Filters
6.6 Other Implementation Methods
6.7 Summary
Problems
7. Nonlinear Filtering
7.1 Chapter Focus
7.2 Quasilinear Filtering
7.3 Sampling Methods for Nonlinear Filtering
7.4 Summary
Problems
8. Practical Considerations
8.1 Chapter Focus
8.2 Detecting and Correcting Anomalous Behavior
8.3 Prefiltering and Data Rejection Methods
8.4 Stability of Kalman Filters
8.5 Suboptimal and Reduced-Order Filters
8.6 Schmidt–Kalman Filtering
8.7 Memory, Throughput, and Wordlength Requirements
8.8 Ways to Reduce Computational Requirements
8.9 Error Budgets and Sensitivity Analysis
8.10 Optimizing Measurement Selection Policies
8.11 Innovations Analysis
8.12 Summary
Problems
9. Applications to Navigation
9.1 Chapter Focus
9.2 Host Vehicle Dynamics
9.3 Inertial Navigation Systems (INS)
9.4 Global Navigation Satellite Systems (GNSS)
9.5 Kalman Filters for GNSS
9.6 Loosely Coupled GNSS/INS Integration
9.7 Tightly Coupled GNSS/INS Integration
9.8 Summary
Problems
Appendix A - MATLAB Software
A.1 Notice
A.2 General System Requirements
A.3 CD Directory Structure
A.4 MATLAB Software for Chapter 2
A.5 MATLAB Software for Chapter 3
A.6 MATLAB Software for Chapter 4
A.7 MATLAB Software for Chapter 5
A.8 MATLAB Software for Chapter 6
A.9 MATLAB Software for Chapter 7
A.10 MATLAB Software for Chapter 8
A.11 MATLAB Software for Chapter 9
A.12 Other Sources of Software
Appendix B - A Matrix Refresher
B.1 Matrix Forms
B.2 Matrix Operations
B.3 Block Matrix Formulas
B.4 Functions of Square Matrices
B.5 Norms
B.6 Cholesky Decomposition
B.7 Orthogonal Decompositions of Matrices
B.8 Quadratic Forms
B.9 Derivatives of MatricesNuméro de notice : 22103 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Monographie Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=63231 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 22103-01 24.20 Livre Centre de documentation Physique Disponible Introduction au problème à trois corps et dynamique linéarisée autour des points de Lagrange, note technique n° 7 du centre de compétence technique "mécanique orbitale" / G. Collange (2006)
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