A GPU implementation of color digital halftoning using the Direct Binary Search algorithm. Chandu, K., Stanich, M., Trager, B., & Wu, C. W. In Circuits and Systems (ISCAS), 2012 IEEE International Symposium on, pages 185-188, May. doi abstract bibtex We illustrate how employing Graphics Processing Units (GPU) can speed-up intensive image processing operations. In particular, we demonstrate the use of the NVIDIA CUDA architecture to implement a color digital binary halftoning algorithm based on Direct Binary Search (DBS). Halftoning a color image is more computationally expensive than the single color case as there is a need to minimize dot interaction between different color planes as well. We propose processing all color planes in parallel. In addition we employ processing several non-overlapping neighborhoods in parallel, by utilizing the GPU's parallel architecture, to further improve the computational efficiency. This parallel approach allows us to use a large neighborhood and filter size, to achieve the highest halftone quality, while having minimal impact on performance.
@inproceedings{6271629,
Author = {Chandu, Kartheek and Stanich, Mikel and Trager, Barry and Chai Wah Wu},
Booktitle = {Circuits and Systems (ISCAS), 2012 IEEE International Symposium on},
Date-Added = {2013-03-22 15:52:05 +0000},
Date-Modified = {2013-03-22 15:52:05 +0000},
Doi = {10.1109/ISCAS.2012.6271629},
Issn = {0271-4302},
Keywords = {Computer architecture;Graphics processing unit;Image color analysis;Instruction sets;Kernel;Parallel processing;Satellite broadcasting},
Pages = {185-188},
Title = {A GPU implementation of color digital halftoning using the Direct Binary Search algorithm},
Year = {May},
Abstract = {We illustrate how employing Graphics Processing Units (GPU) can speed-up intensive image processing operations. In particular, we demonstrate the use of the NVIDIA CUDA architecture to implement a color digital binary halftoning algorithm based on Direct Binary Search (DBS). Halftoning a color image is more computationally expensive than the single color case as there is a need to minimize dot interaction between different color planes as well. We propose processing all color planes in parallel. In addition we employ processing several non-overlapping neighborhoods in parallel, by utilizing the GPU's parallel architecture, to further improve the computational efficiency. This parallel approach allows us to use a large neighborhood and filter size, to achieve the highest halftone quality, while having minimal impact on performance.},
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