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Proceedings Paper

Complex-valued image reconstruction from spectral phase or magnitude
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Paper Abstract

Many significant features of images are represented in their Fourier transform. The spectral phase of an image can often be measured more precisely than magnitude for frequencies of up to a few GHz. However, spectral magnitude is the only measurable data in many imaging applications. In this paper, the reconstruction of complex-valued images from either the phases or magnitudes of their Fourier transform is addressed. Conditions for unique representation of a complex-valued image by its spectral magnitude combined with additional spatial information is investigated and presented. Reconstruction algorithms of complex-valued images are developed and introduced. Three types of reconstruction algorithms are presented. (1) Algorithms that reconstruct a complex-valued image from the magnitude of its discrete Fourier transform and part of its spatial samples based on the autocorrelation function. (2) Iterative algorithms based on the Gerchberg and Saxton approach. (3) Algorithms that reconstruct a complex-valued image from its localized Fourier transform magnitude. The advantages of the proposed algorithms over the presently available approaches are presented and discussed.

Paper Details

Date Published: 23 December 2002
PDF: 9 pages
Proc. SPIE 4792, Image Reconstruction from Incomplete Data II, (23 December 2002); doi: 10.1117/12.451786
Show Author Affiliations
Xiao Qiong Tang, Univ. of Auckland (New Zealand)
Moshe Porat, Univ. of Auckland (New Zealand)

Published in SPIE Proceedings Vol. 4792:
Image Reconstruction from Incomplete Data II
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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