|Title:||The Farthest Point Strategy for Progressive Image Sampling
|Authors:||Yuval Eldar, Michael Lindenbaum, Moshe Porat and Yehoshua Y. Zeevi
|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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