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An efficient O(1) time 3D all nearest neighbor algorithm from image processing perspective
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DOI：10.1016/j.jpdc.2007.06.001.png)
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Abstract
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In this paper, we solve the k-dimensional all nearest neighbor (kD_ANN) problem, where k = 2 or 3, on a linear array with a reconfigurable pipelined bus system (LARPBS) from image processing perspective. First, for a two-dimensional (2D) binary image of size N x N, we devise an algorithm for solving the 2D_ANN problem using a LARPBS of size N2+epsilon, where 0 < epsilon << 1. Then, for a three-dimensional (3D) binary image of size N x N x N, we devise an algorithm for solving the 3D_ANN problem using a LARPBS of size N3+epsilon, where 0 < epsilon < 1. To the best of our knowledge, all results derived above are the best O(1) time 2D_ANN and 3D_ANN algorithms on the LARPBS model known. (C) 2007 Elsevier Inc. All rights reserved.
Keywords:
all nearest neighbors
Euclidean distance transform
LARPBS
image processing
parallel algorithm
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