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Proceedings Paper

Preprocessing and compression of digital holographic images
Author(s): Shuqun Zhang; Mo Chen
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Paper Abstract

Digital hologram compression has recently received increasing attention due to easy acquisition and new applications in three-dimensional information processing. Standard compression algorithms perform poorly on complex-valued holographic data. This paper studies quantization techniques for lossy compression of digital holographic images, where three commonly used quantizers are compared. Our observations show that the real and imagery components of holograms and their corresponding Fourier transform coefficients exhibit a Laplacian and Gaussian distribution, respectively. It is therefore possible to design an optimal quantizer for holographic data compression. To further increase the compression ratio, preprocessing techniques to extract the region of interest are presented. These include Fourier plane filtering and statistical snake image segmentation.

Paper Details

Date Published: 16 September 2005
PDF: 11 pages
Proc. SPIE 5909, Applications of Digital Image Processing XXVIII, 590925 (16 September 2005); doi: 10.1117/12.618599
Show Author Affiliations
Shuqun Zhang, CUNY, College of Staten Island (United States)
Mo Chen, State Univ. of New York at Binghamton (United States)

Published in SPIE Proceedings Vol. 5909:
Applications of Digital Image Processing XXVIII
Andrew G. Tescher, Editor(s)

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