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The theme of this conference is methods and algorithms for reconstructing
images of a physical system or object from remotely-sensed data, in which
the data are incomplete (in the sense that they do not, by themselves,
allow a direct computation of a high-fidelity image). It is therefore
necessary to incorporate other information or constraints to obtain a
useful solution. The design of effective and efficient algorithms for
using the different kinds of available data and constraints to obtain a
solution is of primary importance in these kinds of problems. In many,
although not all, of these problems the data are related to a wavefield
that carries information concerning the object, i.e. they often involve
scattering or diffraction. Example technical areas include phase
retrieval, deconvolution, inverse scattering, regularization, and imaging
through turbulence. Example application areas include radar imaging,
medical imaging (ultrasonic, x-ray CT, MRI, optical diffusion and optical
coherence, etc.), laser imaging, optical and radio astronomy, microscopy,
crystallography, geophysical imaging (atmospheric profiling, ocean
acoustic, seismic, etc.), and signal design. The applications and methods
used are diverse, and we invite contributions from researchers in any
discipline who make use of these kind of techniques.