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Proceedings Paper

Bayesian approach to inverse halftoning
Author(s): Susan M. Thornton; Robert L. Stevenson
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Paper Abstract

There has been a tremendous amount of research in the area of image halftoning. Where the goal has been to find the most visually accurate representation given a limited palette of gray- levels (often just two, black and white). This paper focuses on the inverse problem, that of finding efficient techniques for reconstructing high-quality continuous-tone images from their halftoned versions. The proposed algorithms are based on a maximum a posteriori (MAP) estimation criteria using a Markov random field model for the prior image distribution. Image estimates obtained with the proposed model accurately reconstruct both the smooth regions of the image and the discontinuities along the edges. Algorithms are developed and example gray-level reconstructions are presented generated from both dithered and error diffused halftone originals.

Paper Details

Date Published: 8 September 1993
PDF: 11 pages
Proc. SPIE 1913, Human Vision, Visual Processing, and Digital Display IV, (8 September 1993); doi: 10.1117/12.152702
Show Author Affiliations
Susan M. Thornton, Univ. of Notre Dame (United States)
Robert L. Stevenson, Univ. of Notre Dame (United States)

Published in SPIE Proceedings Vol. 1913:
Human Vision, Visual Processing, and Digital Display IV
Jan P. Allebach; Bernice E. Rogowitz, Editor(s)

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