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Proceedings Paper

Plane-dependent error diffusion on a GPU
Author(s): Yao Zhang; John Ludd Recker; Robert Ulichney; Ingeborg Tastl; John D. Owens
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Paper Abstract

In this paper, we study a plane-dependent technique that reduces dot-on-dot printing in color images, and apply this technique to a GPU-based error diffusion halftoning algorithm. We design image quality metrics to preserve mean color and minimize colorant overlaps. We further use randomized intra-plane error filter weights to break periodic structures. Our GPU implementation achieves a processing speed of 200 MegaPixels/second for RGB color images, and a speedup of 30 - 37x over a multi-threaded implementation on a dual-core CPU. Since the GPU implementation is memory bound, we essentially get the image quality benefits for free by adding arithmetic complexities for inter-plane dependency and error filter weights randomization.

Paper Details

Date Published: 2 February 2012
PDF: 10 pages
Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 829515 (2 February 2012); doi: 10.1117/12.906966
Show Author Affiliations
Yao Zhang, Univ. of California, Davis (United States)
John Ludd Recker, Hewlett-Packard Labs. (United States)
Robert Ulichney, Hewlett-Packard Co. (United States)
Ingeborg Tastl, Hewlett-Packard Labs. (United States)
John D. Owens, Univ. of California, Davis (United States)


Published in SPIE Proceedings Vol. 8295:
Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II
Karen O. Egiazarian; John Recker; Guijin Wang; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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