|
|
|
| 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 |
|---|
|
| Author(s) |
Yao Zhang, John Recker, Robert Ulichney, Ingeborg Tastl, John D. Owens |
|---|
|
| Keyword(s) | Halftoning, Plane-dependent Error Diffusion, Parallel Processing, GPU Computing. |
|---|
|
| Year |
January 2012
|
|---|
| Location | San Francisco, CA |
|---|
| Date | January 23-24, 2012 |
|---|
| Volume | 8295B |
|---|
|
|
| BibTeX |  |
|---|
|
| 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.
|
|---|
|
|
