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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Vol. 17, Iss. 9 — Sep. 1, 2000
  • pp: 1606–1616

Improved-fidelity error diffusion through blending with pseudorandom encoding

Li Ge, Markus Duelli, and Robert W. Cohn  »View Author Affiliations


JOSA A, Vol. 17, Issue 9, pp. 1606-1616 (2000)
http://dx.doi.org/10.1364/JOSAA.17.001606


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Abstract

Error diffusion (ED) and pseudorandom encoding (PRE) methods of designing Fourier transform holograms are compared in terms of their properties and the optical performance of the resulting far-field diffraction patterns. Although both methods produce a diffuse noise pattern due to the error between the desired fully complex pattern and the encoded modulation, the PRE errors reconstruct uniformly over the nonredundant bandwidth of the discrete-pixel spatial light modulator, while the ED errors reconstruct outside the window of the designed diffraction pattern. Combining the two encoding methods produces higher-fidelity diffraction patterns than either method produces individually. For some designs the fidelity of the ED–PRE algorithm is even higher over the entire nonredundant bandwidth than for the previously reported [J. Opt. Soc. Am. A 16, 2425 (1999)] minimum-distance-PRE algorithm.

© 2000 Optical Society of America

OCIS Codes
(030.6600) Coherence and statistical optics : Statistical optics
(070.2580) Fourier optics and signal processing : Paraxial wave optics
(090.1760) Holography : Computer holography
(230.6120) Optical devices : Spatial light modulators

Citation
Li Ge, Markus Duelli, and Robert W. Cohn, "Improved-fidelity error diffusion through blending with pseudorandom encoding," J. Opt. Soc. Am. A 17, 1606-1616 (2000)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-17-9-1606


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  25. To maintain as much consistency as possible in comparing all the curves and tables and to avoid excessive computation, we have calculated and reported all performance met-rics for values of γ=1, 1.1, 1.2, .... This results in adequately smooth and sampled curves except in one case. For the SPRm curve of ED–PRE in Fig. 5, finer sampling led to a significant increase in SPRm, from 53 at γ=1.2 and 1.3 to 60 at γ=1.26. This additional point is included in the plot in Fig. 5. We also checked the maxima of other SPR and SPRm performance curves, using finer sampling increments. However, since the change in appearance is minimal and the maximum values of the curves would change by no more than a few tenths, these additional findings are omitted.

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