| Abstract: |
A new method of "Farthest Point Strategy" (FPS) for
progressive image acquisition - an acquisition process
which enables an approximation of the whole image at
each sampling stage - is presented. Its main
advantage is in retaining its uniformity with the
increased density, providing efficient means for
sparse image sampling and display. In contrast to
previously presented stochastic approaches, the FPS
guarantees the uniformity in a deterministic min-max
sense. Within this uniformity criterion, the sampling
points are irregularly spaced, exhibiting
antialiasing properties comparable to those characteristic
of the best available method (Poisson Disk).
A straightforward modification
of the FPS yields an image-dependent adaptive sampling
scheme. An efficient, $O(N \log N)$ algorithm for both versions is
introduced, and several applications of the FPS are
discussed.
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