
Proceedings Paper
Spectral constraints in the quantization of two-dimensional data distributionsFormat | Member Price | Non-Member Price |
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Paper Abstract
The quantization of an image is connected with the introduction of noise. To adapt the quantized image to the demands of its application constraints can be forced on the spectrum of the noise. But not every spectral constraint can be realized. Coupling mechanisms between the values in the image spectrum limit the realization of spectral constraints. In this paper these limitations are examined for different types of spectral constraints. Amplitude and phase control in portions of the spectrum are treated as well as the use of oversampled spectra during the quantization. Halftoning experiments are shown to illustrate the results.
Paper Details
Date Published: 30 October 1992
PDF: 7 pages
Proc. SPIE 1812, Optical Computing and Neural Networks, (30 October 1992); doi: 10.1117/12.131225
Published in SPIE Proceedings Vol. 1812:
Optical Computing and Neural Networks
Ken Yuh Hsu; Hua-Kuang Liu, Editor(s)
PDF: 7 pages
Proc. SPIE 1812, Optical Computing and Neural Networks, (30 October 1992); doi: 10.1117/12.131225
Show Author Affiliations
Thomas Scheermesser, Univ. Essen (Germany)
Manfred Broja, Univ. Essen (Germany)
Manfred Broja, Univ. Essen (Germany)
Olof Bryngdahl, Univ. Essen (Germany)
Published in SPIE Proceedings Vol. 1812:
Optical Computing and Neural Networks
Ken Yuh Hsu; Hua-Kuang Liu, Editor(s)
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