@inproceedings{Zhang:2012:PED,
| title | = | "Plane-dependent Error Diffusion on a GPU", |
| booktitle | = | "Proceedings of SPIE: IS&T/SPIE Electronic Imaging 2012 / Parallel Processing for Imaging Applications II", |
| author | = | "Yao
Zhang AND John
Recker AND Robert
Ulichney AND Ingeborg
Tastl AND John
D. Owens ", |
| year | = | "2012", |
| month | = | jan, |
| keywords | = | "Halftoning, Plane-dependent Error Diffusion, Parallel Processing, GPU Computing.", |
| volume | = | "8295B", |
| location | = | "San Francisco, CA", |
| eventtime | = | "January 23-24, 2012", |
| 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. ", |
