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Introduction to Imaging from Scattered Fields (Paperback)
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Introduction to Imaging from Scattered Fields (Paperback)
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Obtain the Best Estimate of a Strongly Scattering Object from
Limited Scattered Field Data Introduction to Imaging from Scattered
Fields presents an overview of the challenging problem of
determining information about an object from measurements of the
field scattered from that object. It covers widely used approaches
to recover information about the objects and examines the
assumptions made a priori about the object and the consequences of
recovering object information from limited numbers of noisy
measurements of the scattered fields. The book explores the
strengths and weaknesses of using inverse methods for weak
scattering. These methods, including Fourier-based signal and image
processing techniques, allow more straightforward inverse
algorithms to be exploited based on a simple mapping of scattered
field data. The authors also discuss their recent approach based on
a nonlinear filtering step in the inverse algorithm. They
illustrate how to use this algorithm through numerous
two-dimensional electromagnetic scattering examples. MATLAB (R)
code is provided to help readers quickly apply the approach to a
wide variety of inverse scattering problems. In later chapters of
the book, the authors focus on important and often forgotten
overarching constraints associated with exploiting inverse
scattering algorithms. They explain how the number of degrees of
freedom associated with any given scattering experiment can be
found and how this allows one to specify a minimum number of data
that should be measured. They also describe how the prior discrete
Fourier transform (PDFT) algorithm helps in estimating the
properties of an object from scattered field measurements. The PDFT
restores stability and improves estimates of the object even with
severely limited data (provided it is sufficient to meet a
criterion based on the number of degrees of freedom).
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