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