GPU-enabled parallel processing for image halftoning applications

Programmable Graphics Processing Unit (GPU) has emerged as a powerful parallel processing architecture for various applications requiring a large amount of CPU cycles. In this paper, we study the feasibility for using this architecture for image halftoning, in particular implementing computationally intensive neighborhood halftoning algorithms such as error diffusion and Direct Binary Search (DBS). We show that it is possible to deliver very high performance even for high speed printers.

[1]  Xinxin Wang,et al.  GPU implemention of fast Gabor filters , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

[2]  J.-H. Lee,et al.  Digital color halftoning , 2005, IEEE Signal Processing Magazine.

[3]  C. Wu,et al.  A Unified Framework for Digital Halftoning and Dither Mask Construction : Variations on a Theme and Implementation Issues , 2003 .

[4]  Panagiotis Takis Metaxas,et al.  Parallel digital halftoning by error-diffusion , 2003, PCK50.

[5]  Jan P. Allebach.  DBS: retrospective and future directions , 2000, IS&T/SPIE Electronic Imaging.

[6]  Kevin J. Parker,et al.  Modified approach to the construction of a blue noise mask , 1994, J. Electronic Imaging.

[7]  Jan P. Allebach,et al.  FM screen design using DBS algorithm , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[8]  John F. Jarvis,et al.  A survey of techniques for the display of continuous tone pictures on bilevel displays , 1976 .

[9]  Jan P. Allebach,et al.  Digital halftoning , 2003 .