|Title||Plane-dependent Error Diffusion on a GPU
(In Proceedings) |
|in||Proceedings of SPIE: IS&T/SPIE Electronic Imaging 2012 / Parallel Processing for Imaging Applications II|
Yao Zhang, John Recker, Robert Ulichney, Ingeborg Tastl, John D. Owens |
|Keyword(s)||Halftoning, Plane-dependent Error Diffusion, Parallel Processing, GPU Computing.|
|Location||San Francisco, CA|
|Date||January 23-24, 2012|
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.