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|9 978-0-387-98154-3
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|a 10.1007/978-0-387-98154-3
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|a Solar Image Analysis and Visualization
|h [electronic resource] /
|c edited by Jack Ireland, C. Alex Young.
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|a 1st ed. 2009.
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|a New York, NY :
|b Springer New York :
|b Imprint: Springer,
|c 2009.
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|a IV, 289 p.
|b online resource.
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|a text
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|a 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.
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|a 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 topics were inspired by the Third Solar Image Processing Workshop, held at Trinity College Dublin, Ireland but contributions from other experts have been included as well. This book is mainly aimed at researchers and graduate students working on image processing and compter vision in astronomy and solar physics.
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|a Astrophysics.
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|a Computer vision.
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|a Planetary science.
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|a Signal processing.
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|a Astrophysics.
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|a Computer Vision.
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|a Planetary Science.
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|a Signal, Speech and Image Processing .
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|a Ireland, Jack.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a Young, C. Alex.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9781441931085
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|i Printed edition:
|z 9780387981550
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|i Printed edition:
|z 9780387981536
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|u https://doi.uam.elogim.com/10.1007/978-0-387-98154-3
|z Texto Completo
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|a ZDB-2-PHA
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|a Physics and Astronomy (SpringerNature-11651)
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|a Physics and Astronomy (R0) (SpringerNature-43715)
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