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In [3], a sparsity-driven algorithm to generate high-resolution SA-ISAR images is given, in which a SA-ISAR imaging problem is converted into a sparsity-constrained optimization problem based on the maximum a posteriori estimation.
In this work, we use a linear system of equations to model the SD-OCT measurements, and reconstruct the image from nonuniformly sampled signal via solving an inverse imaging problem.
The digital enhanced RS imaging problem is formally stated as follows: to reconstruct the scene pixel frame image via lexicographical reordering L of the SSP vector estimate estimated from whatever available discrete measurements of the recorded radar/SAR data u.
The enhanced RS imaging problem is stated generally as follows: to map the scene pixel-framed image B ^ via lexicographical reordering B ^ = L - 1 { b ^ } of the SSP vector estimate b ^ reconstructed from whatever available measurements of independent realizations of the recorded data (1).
Project scientists devised measures that enabled them to compensate for the defective mirror and correct the imaging problem.
A final illustration is presented on a real microscopical imaging problem for the classification of cells in serous cytology.
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In the past few years, as the understanding of its theory advanced, AM-FM decompositions have been applied in a series of medical imaging problems ranging from ultrasound to retinal image analysis, yielding excellent results.
In this paper, we consider multi-view imaging problems in which an ensemble of cameras collect images describing a common scene.
Introduction to the mathematics of the Fourier transform and how it arises in a number of imaging problems.
Vessels with small diameters are much liable to effects of diseases and imaging problems.
Although it provides a creative solution to some imaging problems, the method is probably not suitable for widespread medical use at the moment.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com