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

Alison E Shortt; Thomas J Naughton; Bahram Javidi

doi:10.1117/12.505717

23 October 2003 Nonuniform quantization compression of digital holograms of three-dimensional objects using artificial neural networks

Alison E Shortt, Thomas J Naughton, Bahram Javidi

Author Affiliations +

Proceedings Volume 5202, Optical Information Systems; (2003) https://doi.org/10.1117/12.505717
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

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.

Citation Download Citation

Alison E Shortt, Thomas J Naughton, and Bahram Javidi "Nonuniform quantization compression of digital holograms of three-dimensional objects using artificial neural networks", Proc. SPIE 5202, Optical Information Systems, (23 October 2003); https://doi.org/10.1117/12.505717

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