Halftoning and Multitoning

The quickest way of understanding what are halftoning and multitoning is taking a look at wikipedia. Also, I've released the corresponding source codes to my toolkit called pixkit. They are mainly implemented in C++ with OpenCV. Feel free to use them in your research :)

Below are my published papers and I also generate results with some of them to visualize their difference for comparison. The used image, Lion Fish, can be found below.

Lion Fish

pixkit: halftoning and multitoning]

2016 Clustered-dot screen design for digital multitoning

Y. F. Liu and J. M. Guo, “Clustered-dot screen design for multitoning,” IEEE Trans. Image Processing, vol. 25, no. 7, pp. 2971-2982, July 2016.

Abstract:

Digital multitoning is an extension of halftoning for rendering more than two tones at each pixel for higher image quality. Although a lot of effort has been put in generating dispersed dots previously, the blue-noise feature can hardly be achieved for those printers utilizing the electrophotography (EP) process to avoid the physically unstable isolated dots. To overcome this issue, Chandu et al. proposed a screening method for yielding green-noise dot clusters, yet noisy multitone texture was accompanied. This degrades the visual quality and the stability of tone rendering. In this paper, a significantly improved homogeneity of clustered dots can be achieved by the proposed screening method based upon the new inter-iterative clustered-dot direct multi-bit search algorithm. Compared with the former approaches, the inter-iteration design leads to less error by the updated initial multitone patterns. As demonstrated in the experimental results, both of the high homogenous multitone texture and less noisy perception at all absorptance levels are offered in contrast to the former Chandu et al.'s results. The high-quality output proves it as a very competitive candidate for EP printers, e.g., laser printers.

Online resources:

Complete article: [Semantic Scholar], [IEEE Xplore]
Source code: [pixkit]
Trained resources: [data_iCLUDMS2016.xml]
Source image - Lion Fish: [webpage]

2015 Tone-replacement error diffusion for multitoning

J. M. Guo, J. Y. Chang, Y. F. Liu, G. H. Lai, and *J. D. Lee, “Tone-replacement error diffusion for multitoning,” IEEE Trans. Image Processing, vol. 24, no. 11, pp. 43124321, Nov. 2015.

2015 Dot-diffused halftoning with improved homogeneity

Yun-Fu Liu and Jing-Ming Guo, "Dot-diffused halftoning with improved homogeneity," IEEE Trans. Image Processing, vol. 24, no. 11, pp. 4581-4591, Nov. 2015.

Abstract:

Compared to the error diffusion, dot diffusion provides an additional pixel-level parallelism for digital halftoning. However, even though its periodic and blocking artifacts had been eased by previous works, it was still far from satisfactory in terms of the blue noise spectrum perspective. In this work, we strengthen the relationship among the pixel locations of the same processing order by an iterative halftoning method, and the results demonstrate a significant improvement. Moreover, a new approach of deriving the averaged power spectrum density (APSD) is proposed to avoid the regular sampling of the well-known Bartlett's procedure which inaccurately presents the halftone periodicity of certain halftoning techniques with parallelism. As a result, the proposed dot diffusion is substantially superior to the state-of-the-art parallel halftoning methods in terms of visual quality and artifact-free property, and competitive runtime to the theoretical fastest ordered dithering is offered simultaneously.

Online resources:

Complete article [arXiv pre-print]
Source code: [pixkit]
Trained resources: [pixkit]
Source image - Lion Fish: [webpage]

2014 Banding effect removal for digital multitoning

J. Y. Chang, J. M. Guo, and Y. F. Liu, “Banding effect removal for digital multitoning,” International Computer Symposium (ICS), Taichung, Taiwan, Dec. 12-14, 2014.

2014 Content-dependent dot diffusion

Y. F. Liu, J. M. Guo, J. Y. Chang, J. D. Lee, and *H. Lee, “Content-dependent dot diffusion,” International Computer Symposium (ICS), Taichung, Taiwan, Dec. 12-14, 2014.

2013 New class tiling design for dot-diffused halftoning

Yun-Fu Liu and Jing-Ming Guo, "New class tiling design for dot-diffused halftoning," IEEE Trans. Image Processing, vol. 22, no. 3, pp. 1199-1208, March 2013.

Abstract:

In this paper, a new class tiling designed dot diffusion along with the optimized class matrix and diffused matrix are proposed. The result of this method presents a nearly periodic-free halftone when compared to the former schemes. Formerly, the class matrix of the dot diffusion is duplicated and orthogonally tiled to fulfill the entire image for further thresholding and quantized-error diffusion, which accompanies with subsequent periodic artifacts. In our observation, this artifact can be solved by manipulating the class tiling with comprising rotation, transpose, and alternatively shifting of the class matrices. As documented in the experimental results, the proposed dot diffusion has been compared with the former halftoning methods with parallelism in terms of image quality, processing efficiency, periodicity, and memory consumption; the proposed dot diffusion exhibits as a very competitive candidate in printing/display market.

Online resources:

Complete article [pdf file]
Source code [pixkit]

2013 Efficient halftoning based on multiple look-up tables

Jing-Ming Guo, Yun-Fu Liu, Jla-Yu Chang, and Jiann-Der Lee, "Efficient halftoning based on multiple look-up tables," IEEE Trans. Image Processing, vol. 22, no. 11, Nov. 2013.

Abstract:

Look-up table (LUT) halftoning is an efficient way to construct halftone images and approximately simulate the dot distribution of the learned halftone image set. In this paper, a general mechanism named multiple look-up table (MLUT) halftoning is proposed to generate the halftones of direct binary search (DBS), whereas the high efficient characteristic of the LUT is still preserved. In the MLUT, the standard deviation is adopted as an important feature to classify various tables. In addition, the proposed quick standard deviation evaluation is employed to yield an extremely low computational complexity in calculating the standard deviation. In the parameter optimization, the autocorrelation is adopted because it can fully characterize the periodicity of dot distribution. Experimental results demonstrate that the dot distribution generated by the proposed method approximates to that of the DBS, which enables the proposed scheme as a very competitive candidate in the copying and printing industry.

Online resources:

Complete article [pdf file]

2012 High efficient direct binary search using multiple lookup tables

J. M. Guo, Y. F. Liu, and J. Y. Chang, “High efficient direct binary search using multiple lookup tables,” IEEE International Conference on Image Processing (ICIP), Florida, U.S.A., pp. 813-816, Sep. 30 - Oct. 3, 2012.

2011 Semi-aperiodic dot diffusion

Y. F. Liu and *J. M. Guo, “Semi-aperiodic dot diffusion,” IEEE International Symposium on Circuits and Systems (ISCAS), Rio de Janeiro, Brazil, May 15-18, 2011.

2009 Improved dot diffusion by diffused matrix and class matrix co-optimization

Jing-Ming Guo and Yun-Fu Liu, "Improved dot diffusion by diffused matrix and class matrix co-optimization," IEEE Trans. Image Processing, vol. 18, no. 8, pp. 1804-1816, August 2009.

Abstract:

Dot diffusion is an efficient approach which utilizes concepts of block-wise and parallel-oriented processing to generate halftones. However, the block-wise nature of processing reduces image quality much more significantly as compared to error diffusion. In this work, four types of filters with various sizes are employed in co-optimization procedures with class matrices of size 8x8 and 16x16 to improve the image quality. The optimal diffused weighting and area are determined through simulations. Many well-known halftoning methods, some of which includes direct binary search (DBS), error diffusion, ordered dithering, and prior dot diffusion methods, are also included for comparisons. Experimental results show that the proposed dot diffusion achieved quality close to some forms of error diffusion, and additionally, superior to the well-known Jarvis and Stucki error diffusion and Mese’s dot diffusion. Moreover, the inherent parallel processing advantage of dot diffusion is preserved, allowing us to reap higher executing efficiency than both DBS and error diffusion.

Online resources:

Complete article [pdf file]
Source code [pixkit]

Google Sites

Report abuse