Articles liés à Mathematical Models for Remote Sensing Image Processing:...
Mathematical Models for Remote Sensing Image Processing: Models and Methods for the Analysis of 2D Satellite and Aerial Images - Couverture souple
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Synopsis
Mathematical models and methods for remote sensing image analysis: an introduction.- Models for hyperspectral image analysis: from unmixing to object-based classification.- Very high spatial resolution optical imagery: tree-based methods and multi-temporal models for mining and analysis.- Very high resolution and interferometric SAR: Markovian and patch-based non-local mathematical models.- Polarimetric SAR modelling: Mellin kind statistics and time-frequency analysis.- Remote sensing data fusion: guided filter-based hyperspectral pansharpening and graph-based feature-level fusion.- "Remote sensing data fusion: Markov models and mathematical morphology for multisensor, multiresolution, and multiscale image classification.- Change detection in multitemporal images through single-and multi-scale approaches.- Satellite image time series: mathematical models for data mining and missing data restoration.- Advances in kernel machines for image classification and biophysical parameter retrieval.
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