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Image Shrinking and Expanding on a Pyramid
November 1993 (vol. 4 no. 11)
pp. 1291-1296

Develops two algorithms to perform the q step shrinking and expanding of an N*N binary image on a pyramid computer with an N*N base. The time complexity of both algorithms is O( square root q). However, one uses O( square root q) space per processor, while the per-processor space requirement of the other is O(1).

[1] J. Jenq and S. Sahni, "Reconfigurable mesh algorithms for image shrinking, expanding, clustering, and template matching," inProc. Int. Parallel Processing Symp., 1991, pp. 208-215.
[2] S. Ranks and S. Sahni, "Hypercube algorithms for image transformations," inProc. 1989 Int. Conf. Parallel Processing, pp. 24-31.
[3] Ranka, S., and S. Sahni,Hypercube Algorithms for Image Processing and Pattern Recognition, Springer-Verlag, Berlin, 1990.
[4] A. Rosenfeld and A. Kak,Digital Picture Processing, New York: Academic, 1976.
[5] A. Rosenfeld, "A note on shrinking and expanding operations in pyramids,"Pattern Recognition Lett., pp. 241-244, 1987.

Index Terms:
Index Termsshrinking; expanding; binary image; pyramid computer; time complexity; spacecomplexity; computational complexity; image processing; multiprocessor interconnectionnetworks; parallel algorithms
Citation:
J.F. Jenq, S. Sahni, "Image Shrinking and Expanding on a Pyramid," IEEE Transactions on Parallel and Distributed Systems, vol. 4, no. 11, pp. 1291-1296, Nov. 1993, doi:10.1109/71.250106
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