| GEOL1042-1 | |||||
| Geological imaging and inverse modeling | |||||
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Durée :
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| 30h Th, 10h Pr, 30h Proj. | |||||
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Nombre de crédits :
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Nom du professeur :
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| Frédéric Nguyen, Eric Pirard | |||||
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Langue(s) du cours :
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| Langue anglaise | |||||
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Organisation et évaluation :
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| Enseignement au premier quadrimestre, examen en janvier | |||||
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Unités d'enseignement prérequises et corequises :
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| Les unités prérequises ou corequises sont présentées au sein de chaque programme | |||||
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Contenus du cours :
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| 1. Introduction to Image Analysis and Stereology Induction vs deduction The importance of vision in geosciences Stereology and applied mineralogy 2. From minerals to pixels : basic principles of imaging What is an image? 2D scanning geometry for imaging 3D surface imaging 3D volume imaging Scientific imaging in microscopy Image calibration From analog to digital images Digital image file formats 3. Physics of Remote Sensing. Electromagnetic radiation. Radiance and reflectance. Sources of electromagnetic radiation Atmospheric corrections, calibration methods Spectral properties of minerals, rocks and soils VNIR and SWIR ranges Multispectral, superspectral and hyperspectral remote sensing 4. Technology of Earth Observation : platforms and sensors. Orbital properties. Scanning systems. Spatial characteristics of RS data. Spectral characteristics of RS data. Examples: Landsat TM and ETM+, SPOT 3-4-5, ASTER, IKONOS, QuickBird, CASI, AVIRIS, HyMap. 5. Image Processing Image processing operations (global vs. local) Linear filters (low-pass, hi-pass, gradients) Mathematical Morphology (erosion, dilation, opening, closing) Spectral classification tools (thresholding, µgaussian, ...) Geodesic operators and distance functions Spatial segmentation (labelling, hole-fill, watershed, SKIZ,...) Introduction to mixed (spectro-spatial) segmentation 6. Image analysis and processing, optical VNIR SWIR and thermal domains. Preprocessing. Geometric corrections, georeferencing. Radiometric correction, calibrations, atmospheric corrections Multispectral data processing. Data fusion, image sharpening Band ratios, indexes Data transforms: principal components analysis, Munssell HIS. Classification techniques. Spatial filtering. Convolution filters. Texture Fourrier transform 7. Quantitative mineralogical and textural analysis Modal (phase) and porosity analysis Blob analysis: particle size and shape analysis Network analysis: Characterizing size distributions in a continuous phase. Quantitative microstructural and textural analysis: characterizing spatial arrangement | |||||
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Acquis d'apprentissage (objectifs d'apprentissage) du cours :
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| To give students a full overview of image processing and analysis in the geosciences To familiarize students with the main techniques for image acquisition and image processing with a particular emphasis on mathematical morphology To give students the possibility to practice digital imaging and develop their critical perception of applications in geology To provide guidelines for selecting appropriate hardware and software tools to solve a given problem. | |||||
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Activités d'apprentissage prévues et méthodes d'enseignement :
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Mode d'enseignement (présentiel ; enseignement à distance) :
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Lectures recommandées ou obligatoires et notes de cours :
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| Supports didactiques mis à disposition sour forme pdf (cf portail) PIRARD E., SARDINI P., Image analysis for advanced characterization of geomaterials, EMU Lecture Notes, 2009 PIRARD, E., 2004, Chapter IV. Image measurements in P. FRANCUS (Ed) "Image analysis, sediments and paleoenvironmental reconstruction", Kluwer, NY PIRARD, E. et CACERES, F., 2004, Télédétection et télégestion des informations géologiques : de nouvelles technologies au service du développement. L'exemple du Sud Lipez (Bolivie). | |||||
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Modalités d'évaluation et critères :
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Contacts :
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