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This book maximizes reader insights into the field of mathematical
models and methods for the processing of two-dimensional remote
sensing images. It presents a broad analysis of the field,
encompassing passive and active sensors, hyperspectral images,
synthetic aperture radar (SAR), interferometric SAR, and
polarimetric SAR data. At the same time, it addresses highly
topical subjects involving remote sensing data types (e.g., very
high-resolution images, multiangular or multiresolution data, and
satellite image time series) and analysis methodologies (e.g.,
probabilistic graphical models, hierarchical image representations,
kernel machines, data fusion, and compressive sensing) that
currently have primary importance in the field of mathematical
modelling for remote sensing and image processing. Each chapter
focuses on a particular type of remote sensing data and/or on a
specific methodological area, presenting both a thorough analysis
of the previous literature and a methodological and experimental
discussion of at least two advanced mathematical methods for
information extraction from remote sensing data. This organization
ensures that both tutorial information and advanced subjects are
covered. With each chapter being written by research scientists
from (at least) two different institutions, it offers multiple
professional experiences and perspectives on each subject. The book
also provides expert analysis and commentary from leading remote
sensing and image processing researchers, many of whom serve on the
editorial boards of prestigious international journals in these
fields, and are actively involved in international scientific
societies. Providing the reader with a comprehensive picture of the
overall advances and the current cutting-edge developments in the
field of mathematical models for remote sensing image analysis,
this book is ideal as both a reference resource and a textbook for
graduate and doctoral students as well as for remote sensing
scientists and practitioners.
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Energy Minimization Methods in Computer Vision and Pattern Recognition - 4th International Workshop, EMMCVPR 2003, Lisbon, Portugal, July 7-9, 2003, Proceedings (Paperback, 2003 ed.)
Anand Rangarajan, Mario A.T. Figueiredo, Josiane Zerubia
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R3,224
Discovery Miles 32 240
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 4th International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2003, held in Lisbon, Portugal in July 2003. The 33 revised full papers presented were carefully reviewed and selected from 66 submissions. The papers are organized in topical sections on unsupervised learning and matching, probabilistic modeling, segmentation and grouping, shape modeling, restoration and reconstruction, and graphs and graph-based methods.
This volume consists of the 42 papers presented at the
International Workshop on Energy Minimization Methods in Computer
Vision and Pattern Recognition (EMMCVPR2001),
whichwasheldatINRIA(InstitutNationaldeRechercheen Informatique et
en Automatique) in Sophia Antipolis, France, from September 3
through September 5, 2001. This workshop is the third of a series,
which was started with EMMCVPR'97, held in Venice in May 1997, and
continued with EMMCVR'99, which took place in York, in July 1999.
Minimization problems and optimization methods permeate computer
vision (CV), pattern recognition (PR), and many other ?elds of
machine intelligence. The aim of the EMMCVPR workshops is to bring
together people with research interests in this interdisciplinary
topic. Although the subject is traditionally well represented at
major international conferences on CV and PR, the EMMCVPR workshops
provide a forum where researchers can report their recent work and
engage in more informal discussions. We received 70 submissions
from 23 countries, which were reviewed by the members of the
program committee. Based on the reviews, 24 papers were - cepted
for oral presentation and 18 for poster presentation. In this
volume, no distinction is made between papers that were presented
orally or as posters. The book is organized into ?ve sections,
whose topics coincide with the ?ve s- sionsoftheworkshop:
"ProbabilisticModelsandEstimation,""ImageModelling and Synthesis,"
"Clustering, Grouping, and Segmentation," "Optimization and
Graphs," and "Shapes, Curves, Surfaces, and Templates."
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