Image halftoning and inverse halftoning for optimized dot diffusion. Mese, M. & Vaidyanathan, P. In Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on, volume 2, pages 54 -58 vol.2, 10, 1998. doi abstract bibtex The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error diffusion method. However, the image quality offered by error diffusion is still regarded as superior to other known methods. In a previous paper we showed how the dot diffusion method can be improved by optimization of the so-called class matrix. In this paper we first review the dot diffusion algorithm and the optimization of the class matrix. A method for inverse halftoning of dot diffused images is then proposed. The method uses wavelet decomposition to eliminate the halftoning noise and does not make use of the knowledge of the class matrix
@inproceedings{723316,
Author = {Mese, M. and Vaidyanathan, P.P.},
Booktitle = {Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on},
Date-Added = {2012-08-20 14:17:27 +0000},
Date-Modified = {2012-08-20 17:25:50 +0000},
Doi = {10.1109/ICIP.1998.723316},
Keywords = {blue noise;class matrix optimization;digital halftoning;dot diffusion algorithm;error diffusion method;halftoning noise elimination;image halftoning;image quality;inverse halftoning;optimized dot diffusion;wavelet decomposition;image processing;matrix algebra;noise;optimisation;wavelet transforms;},
Month = {10},
Pages = {54 -58 vol.2},
Title = {Image halftoning and inverse halftoning for optimized dot diffusion},
Volume = {2},
Year = {1998},
Abstract = {The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error diffusion method. However, the image quality offered by error diffusion is still regarded as superior to other known methods. In a previous paper we showed how the dot diffusion method can be improved by optimization of the so-called class matrix. In this paper we first review the dot diffusion algorithm and the optimization of the class matrix. A method for inverse halftoning of dot diffused images is then proposed. The method uses wavelet decomposition to eliminate the halftoning noise and does not make use of the knowledge of the class matrix},
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