Solar Image Analysis and Visualization
This volume presents a selection of papers on the state of the art of image enhancement, automated feature detection, machine learning, and visualization tools in support of solar physics that focus on the challenges presented by new ground-based and space-based instrumentation. The articles and top...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
New York, NY :
Springer New York,
2009.
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Preface: A Topical Issue on Solar Image Analysis and Visualization
- FESTIVAL: A Multiscale Visualization Tool for Solar Imaging Data
- Visualization of Distributed Solar Data and Metadata with the Solar Weather Browser
- Widespread Occurrence of Trenching Patterns in the Granulation Field: Evidence for Roll Convection?
- Principal Components and Independent Component Analysis of Solar and Space Data
- Automatic Recognition and Characterisation of Supergranular Cells from Photospheric Velocity Fields
- Automated McIntosh-Based Classification of Sunspot Groups Using MDI Images
- Multifractal Properties of Evolving Active Regions
- Multiscale Analysis of Active Region Evolution
- A Comparison of Feature Classification Methods for Modeling Solar Irradiance Variation
- The Observed Long- and Short-Term Phase Relation between the Toroidal and Poloidal Magnetic Fields in Cycle 23
- Comparison of Five Numerical Codes for Automated Tracing of Coronal Loops
- Segmentation of Loops from Coronal EUV Images
- The Pixelised Wavelet Filtering Method to Study Waves and Oscillations in Time Sequences of Solar Atmospheric Images
- A Time-Evolving 3D Method Dedicated o the Reconstruction of Solar Plumes and Results Using Extreme Ultraviolet Data
- Automatic Detection and Classification of Coronal Holes and Filaments Based on EUV and Magnetogram Observations of the Solar Disk
- Spatial and Temporal Noise in Solar EUV Observations
- Multiscale Edge Detection in the Corona
- Automated Prediction of CMEs Using Machine Learning of CME?–?Flare Associations
- Automatic Detection and Tracking of Coronal Mass Ejections in Coronagraph Time Series.