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Mathematical Methods for Signal and Image Analysis and
Representation presents the mathematical methodology for generic
image analysis tasks. In the context of this book an image may be
any m-dimensional empirical signal living on an n-dimensional
smooth manifold (typically, but not necessarily, a subset of
spacetime). The existing literature on image methodology is rather
scattered and often limited to either a deterministic or a
statistical point of view. In contrast, this book brings together
these seemingly different points of view in order to stress their
conceptual relations and formal analogies. Furthermore, it does not
focus on specific applications, although some are detailed for the
sake of illustration, but on the methodological frameworks on which
such applications are built, making it an ideal companion for those
seeking a rigorous methodological basis for specific algorithms as
well as for those interested in the fundamental methodology per se.
Covering many topics at the forefront of current research,
including anisotropic diffusion filtering of tensor fields, this
book will be of particular interest to graduate and postgraduate
students and researchers in the fields of computer vision, medical
imaging and visual perception.
Mathematical Methods for Signal and Image Analysis and
Representation presents the mathematical methodology for generic
image analysis tasks. In the context of this book an image may be
any m-dimensional empirical signal living on an n-dimensional
smooth manifold (typically, but not necessarily, a subset of
spacetime). The existing literature on image methodology is rather
scattered and often limited to either a deterministic or a
statistical point of view. In contrast, this book brings together
these seemingly different points of view in order to stress their
conceptual relations and formal analogies. Furthermore, it does not
focus on specific applications, although some are detailed for the
sake of illustration, but on the methodological frameworks on which
such applications are built, making it an ideal companion for those
seeking a rigorous methodological basis for specific algorithms as
well as for those interested in the fundamental methodology per se.
Covering many topics at the forefront of current research,
including anisotropic diffusion filtering of tensor fields, this
book will be of particular interest to graduate and postgraduate
students and researchers in the fields of computer vision, medical
imaging and visual perception.
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