Share Email Print

Proceedings Paper

Iterative and noniterative nonuniform quantisation techniques in digital holography
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Compression is essential for efficient storage and transmission of three-dimensional (3D) digital holograms. The inherent speckle content in holographic data causes lossless compression techniques, such as Huffman and Burrows-Wheeler (BW), to perform poorly. Therefore, the combination of lossy quantisation followed by lossless compression is essential for effective compression of digital holograms. Our complex-valued digital holograms of 3D real-world objects were captured using phase-shift interferometry (PSI). Quantisation reduces the number of different real and imaginary values required to describe each hologram. Traditional data compression techniques can then be applied to the hologram to actually reduce its size. Since our data has a nonuniform distribution, the uniform quantisation technique does not perform optimally. We require nonuniform quantisation, since in a histogram representation our data is denser around the origin (low amplitudes), thus requiring more cluster centres, and sparser away from the origin (high amplitudes). By nonuniformly positioning the cluster centres to match the fact that there is a higher probability that the pixel will have a low amplitude value, the cluster centres can be used more efficiently. Nonuniform quantisation results in cluster centres that are adapted to the exact statistics of the input data. We analyse a number of iterative (k-means clustering, Kohonen competitive neural network, SOM, and annealed Hopfield neural network), and non-iterative (companding, histogram, and optimal) nonuniform quantisation techniques. We discuss the strengths and weaknesses of each technique and highlight important factors that must be considered when choosing between iterative and non-iterative nonuniform quantisation. We measure the degradation due to lossy quantisation in the reconstruction domain, using the normalised rms (NRMS) metric.

Paper Details

Date Published: 25 April 2006
PDF: 12 pages
Proc. SPIE 6187, Photon Management II, 618719 (25 April 2006); doi: 10.1117/12.662994
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. 6187:
Photon Management II
John T. Sheridan; Frank Wyrowski, Editor(s)

© SPIE. Terms of Use
Back to Top