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Proceedings Paper

Nonuniform quantization compression of digital holograms of three-dimensional objects using artificial neural networks
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Paper Abstract

We propose two lossy data compression techniques for complex-valued digital holograms of three-dimensional objects. The techniques employ unsupervised artificial neural networks to nonuniformly quantize the real and imaginary values of digital holograms. The digital holograms of real-world three-dimensional objects were captured using phase-shift interferometry. Our techniques are compared experimentally with the uniform quantization approach, and with an alternative nonuniform quantization technique based on the k-means clustering algorithm.

Paper Details

Date Published: 23 October 2003
PDF: 7 pages
Proc. SPIE 5202, Optical Information Systems, (23 October 2003); doi: 10.1117/12.505717
Show Author Affiliations
Alison E Shortt, National Univ. of Ireland, Maynooth (Ireland)
Thomas J Naughton, National Univ. of Ireland, Maynooth (Ireland)
Bahram Javidi, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 5202:
Optical Information Systems
Bahram Javidi; Demetri Psaltis, Editor(s)

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