Relevant bibliographies by topics / Halftoning

Academic literature on the topic 'Halftoning'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Halftoning"

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Chen, Guang Xue, Qi Feng Chen, Jing Lei Tai, and Jiang Wen Liu. "Halftoning Method and Reproduction of Color Gamut in Digital Image Output." Applied Mechanics and Materials 421 (September 2013): 138–43. http://dx.doi.org/10.4028/www.scientific.net/amm.421.138.

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Image halftoning is the core technique of digital image output, which determines the quality of the color and tonal gradation reproduction. In this paper, the existing halftoning techniques were analyzed and evaluated, such as FM halftoning and AM halftoning, etc. And a new halftoning mode, frequency conversion amplitude modulation (FCAM), was proposed. This method is still based on AM halftoning, but it uses the different screen frequency for halftoning image of the different color version, so as to avoid moiré fringes on the smaller superposition angle. The use of new halftoning model can achieve halftoning image output which is more than 4 colors (such as 6 colors or 7 colors) without visual moirè pattern when overprinting. By the new technique, high-fidelity printing is achieved, and the color gamut of the output image is expanded, and we can get more vivid realistic effect of image transmission. We tested color gamut expansion of 6 colors and 7 colors high-fidelity printing, and obtained the expected conclusion by quantitative analysis.
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Ortega-Sánchez, Noé, Diego Oliva, Erik Cuevas, Marco Pérez-Cisneros, and Angel A. Juan. "An Evolutionary Approach to Improve the Halftoning Process." Mathematics 8, no. 9 (September 22, 2020): 1636. http://dx.doi.org/10.3390/math8091636.

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The techniques of halftoning are widely used in marketing because they reduce the cost of impression and maintain the quality of graphics. Halftoning converts a digital image into a binary image conformed by dots. The output of the halftoning contains less visual information; a possible benefit of this task is the reduction of ink when graphics are printed. The human eye is not able to detect the absence of information, but the printed image stills have good quality. The most used method for halftoning is called Floyd-Steinberger, and it defines a specific matrix for the halftoning conversion. However, most of the proposed techniques in halftoning use predefined kernels that do not permit adaptation to different images. This article introduces the use of the harmony search algorithm (HSA) for halftoning. The HSA is a popular evolutionary algorithm inspired by the musical improvisation. The different operators of the HSA permit an efficient exploration of the search space. The HSA is applied to find the best configuration of the kernel in halftoning; meanwhile, as an objective function, the use of the structural similarity index (SSIM) is proposed. A set of rules are also introduced to reduce the regular patterns that could be created by non-appropriate kernels. The SSIM is used due to the fact that it is a perception model used as a metric that permits comparing images to interpret the differences between them numerically. The aim of combining the HSA with the SSIM for halftoning is to generate an adaptive method that permits estimating the best kernel for each image based on its intrinsic attributes. The graphical quality of the proposed algorithm has been compared with classical halftoning methodologies. Experimental results and comparisons provide evidence regarding the quality of the images obtained by the proposed optimization-based approach. In this context, classical algorithms have a lower graphical quality in comparison with our proposal. The results have been validated by a statistical analysis based on independent experiments over the set of benchmark images by using the mean and standard deviation.
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Mao, Ruiyi, Utpal Sarkar, Robert Ulichney, and Jan P. Allebach. "3D Halftoning." Electronic Imaging 2017, no. 18 (January 29, 2017): 147–55. http://dx.doi.org/10.2352/issn.2470-1173.2017.18.color-048.

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Schmaltz, Christian, Pascal Gwosdek, Andrés Bruhn, and Joachim Weickert. "Electrostatic Halftoning." Computer Graphics Forum 29, no. 8 (November 10, 2010): 2313–27. http://dx.doi.org/10.1111/j.1467-8659.2010.01716.x.

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Miceli, Christopher M. "Inverse halftoning." Journal of Electronic Imaging 1, no. 2 (April 1, 1992): 143. http://dx.doi.org/10.1117/12.57675.

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Allebach, J., and T. Pappas. "Digital halftoning." IEEE Signal Processing Magazine 20, no. 4 (July 2003): 12–13. http://dx.doi.org/10.1109/msp.2003.1215227.

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Zhaohui Sun. "Video halftoning." IEEE Transactions on Image Processing 15, no. 3 (March 2006): 678–86. http://dx.doi.org/10.1109/tip.2005.863023.

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G Freeman, K. "Digital halftoning." Displays 9, no. 3 (July 1988): 149. http://dx.doi.org/10.1016/0141-9382(88)90011-x.

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Shapiro, Linda. "Digital halftoning." Computer Vision, Graphics, and Image Processing 41, no. 3 (March 1988): 382. http://dx.doi.org/10.1016/0734-189x(88)90109-0.

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Li, Mei, Erhu Zhang, Yutong Wang, Jinghong Duan, and Cuining Jing. "Inverse Halftoning Methods Based on Deep Learning and Their Evaluation Metrics: A Review." Applied Sciences 10, no. 4 (February 23, 2020): 1521. http://dx.doi.org/10.3390/app10041521.

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Inverse halftoning is an ill-posed problem that refers to the problem of restoring continuous-tone images from their halftone versions. Although much progress has been achieved over the last decades, the restored images still suffer from detail loss and visual artifacts. Recent studies show that inverse halftoning methods based on deep learning are superior to other traditional methods, and thus this paper aimed to systematically review the inverse halftone methods based on deep learning, so as to provide a reference for the development of inverse halftoning. In this paper, we firstly proposed a classification method for inverse halftoning methods on the basis of the source of halftone images. Then, two types of inverse halftoning methods for digital halftone images and scanned halftone images were investigated in terms of network architecture, loss functions, and training strategies. Furthermore, we studied existing image quality evaluation including subjective and objective evaluation by experiments. The evaluation results demonstrated that methods based on multiple subnetworks and methods based on multi-stage strategies are superior to other methods. In addition, the perceptual loss and the gradient loss are helpful for improving the quality of restored images. Finally, we gave the future research directions by analyzing the shortcomings of existing inverse halftoning methods.
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Dissertations / Theses on the topic "Halftoning"

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Aijazi, Ahmed Tausif. "Hybrid Color Halftoning." Thesis, Linköping University, Department of Science and Technology, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-56737.

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Halftoning methods can be divided into two main categories, namely AM (Amplitude Modulated) and FM (Frequency Modulated). Some printing methods, such as Flexography, are not able to produce dots small enough to handle the highlights and the shadows of the original image by just using AM halftoning method. To overcome this problem FM method is used in the highlights (and the shadows) and an AM method in rest of the image.

Hybrid halftoning (combination of AM and FM) technique for grayscale images has already be presented showing the best way to place FM and AM dots in the resulting binary image. This thesis work is and extension of that and presents hybrid technique for color images. In color images, besides the problem of transition area between AM and FM, a number of other factors needs to be addressed. One of such factors is to define the starting point of FM technique in different color channels. In this work all the possibilities of combining AM and FM in different color channels have been investigated and then the best approach for hybrid color halftoning is proposed. This approach not only uses the best solution for starting point of FM halftoning in each channel but also places the different color dots in the highlights, as homogenously as possible.

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Streit, Lisa M. "Importance driven halftoning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ34422.pdf.

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Gustavsson, Oscar. "Inverse Halftoning Using Inverse Methods." Thesis, Linköpings universitet, Institutionen för teknik och naturvetenskap, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-96225.

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This Master´s thesis discusses the problems concerning inverse halftoning, which means converting a halftone image into a continuous tone one. The thesis evaluates the use of inverse methods, showing promising results. The algorithm is implemented and tested using Matlab and serves as a prototype for possible full scale applications. The work is based upon previously published articles on the subject, along with basic halftoning and printing theory. This serves as a starting point from which the proposed method is developed, and the results are in some areas competitive against other, previously published approaches.
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Liu, Chen. "Multilevel halftoning over hexagonal grids." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file 0.85 Mb., 47 p, 2006. http://wwwlib.umi.com/dissertations/fullcit/1435813.

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Veryovka, Oleg. "Texture control in digital halftoning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0016/NQ46940.pdf.

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Gooran, Sasan. "High quality frequency modulated halftoning /." Norrköping : Univ, 2001. http://www.bibl.liu.se/liupubl/disp/disp2001/tek668s.pdf.

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莫紹祥 and Siu-cheung Mok. "Parametric halftoning and image reconstruction." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1988. http://hub.hku.hk/bib/B31208800.

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Mok, Siu-cheung. "Parametric halftoning and image reconstruction /." [Hong Kong : University of Hong Kong], 1988. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1243713X.

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Ulichney, Robert. "Digital halftoning and the physical reconstruction function." Thesis, Massachusetts Institute of Technology, 1986. http://hdl.handle.net/1721.1/15079.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1986.
MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING
Bibliography: p. 397-405.
by Robert A. Ulichney.
Ph.D.
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Dong, Chen-Koung. "Measurement of printer parameters for model-based halftoning." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/12812.

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Books on the topic "Halftoning"

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Ulichney, Robert. Digital halftoning. Cambridge, Mass: MIT Press, 1987.

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Lau, Daniel L. Modern digital halftoning. 2nd ed. Boca Raton: CRC Press, 2008.

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R, Arce Gonzalo, ed. Modern digital halftoning. New York: M. Dekker, 2001.

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R, Arce Gonzalo, ed. Modern digital halftoning. 2nd ed. Boca Raton: CRC Press, 2008.

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Lau, Daniel L. Modern digital halftoning. 2nd ed. Boca Raton: CRC Press, 2008.

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Ulichney, R. Digital halftoning. MIT, 1987.

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Arce, Gonzalo R., and Daniel L. Lau. Modern Digital Halftoning. Taylor & Francis Group, 2018.

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Arce, Gonzalo R., and Daniel L. Lau. Modern Digital Halftoning. Taylor & Francis Group, 2018.

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Arce, Gonzalo R., and Daniel L. Lau. Modern Digital Halftoning. Taylor & Francis Group, 2018.

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Lau, Daniel L., and Gonzalo R. Arce. Modern Digital Halftoning. Edited by Daniel L. Lau and Gonzalo R. Arce. CRC Press, 2018. http://dx.doi.org/10.1201/9781315219790.

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Book chapters on the topic "Halftoning"

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Kuznetsov, Yuri V. "Halftoning." In Principles of Image Printing Technology, 67–94. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-60955-9_4.

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Cole, A. J. "Naive Halftoning." In CG International ’90, 203–22. Tokyo: Springer Japan, 1990. http://dx.doi.org/10.1007/978-4-431-68123-6_13.

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Gomes, Jonas, and Luiz Velho. "Digital Halftoning." In Image Processing for Computer Graphics, 217–46. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2745-6_8.

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Velho, Luiz, Alejandro Frery, and Jonas Gomes. "Digital Halftoning." In Texts in Computer Science, 313–44. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84800-193-0_12.

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Yan, Bin, Yong Xiang, and Guang Hua. "Digital Halftoning." In Improving Image Quality in Visual Cryptography, 35–53. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8289-5_3.

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Deussen, Oliver, and Tobias Isenberg. "Halftoning and Stippling." In Computational Imaging and Vision, 45–61. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4519-6_3.

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Lou, Qun, and Peter Stucki. "Fundamentals of 3D halftoning." In Electronic Publishing, Artistic Imaging, and Digital Typography, 224–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0053273.

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Gu, Jianjin, and Li Li. "A New Method of Halftoning and Inverse Halftoning Based on GAN Network." In Advances in Artificial Intelligence and Security, 119–31. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78615-1_11.

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Leondes, Cornelius T. "Digital Halftoning Algorithms for Medical Imaging." In Computational Methods in Biophysics, Biomaterials, Biotechnology and Medical Systems, 127–92. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/0-306-48329-7_4.

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Liu, Yun-Fu, Jing-Ming Guo, and Jiann-Der Lee. "Inverse Halftoning Based on Bayesian Theorem." In Advances in Image and Video Technology, 130–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92957-4_12.

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Conference papers on the topic "Halftoning"

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Anderson, Peter G., and Changmeng Liu. "Compressible halftoning." In Electronic Imaging 2003, edited by Reiner Eschbach and Gabriel G. Marcu. SPIE, 2003. http://dx.doi.org/10.1117/12.472881.

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Stucki, Peter. "3D halftoning." In Advanced Imaging and Network Technologies, edited by Jan Bares, Christopher T. Bartlett, Paul A. Delabastita, Jose L. Encarnacao, Nelson V. Tabiryan, Panos E. Trahanias, and Arthur R. Weeks. SPIE, 1997. http://dx.doi.org/10.1117/12.266339.

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Mese, Murat, and Palghat P. Vaidyanathan. "New methods for digital halftoning and inverse halftoning." In Electronic Imaging 2002, edited by Reiner Eschbach and Gabriel G. Marcu. SPIE, 2001. http://dx.doi.org/10.1117/12.452998.

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Pang, Wai-Man, Yingge Qu, Tien-Tsin Wong, Daniel Cohen-Or, and Pheng-Ann Heng. "Structure-aware halftoning." In ACM SIGGRAPH 2008 papers. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1399504.1360688.

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Felix Yu, S. K., Yuk-Hee Chan, P. K. Daniel Lun, Chi Wang Jeffrey Chan, and Kai Wang Kenneth Li. "Colorblind-friendly Halftoning." In 2018 26th European Signal Processing Conference (EUSIPCO). IEEE, 2018. http://dx.doi.org/10.23919/eusipco.2018.8553352.

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Pappas, Thrasyvoulos N., and David L. Neuhoff. "Model-based halftoning." In Electronic Imaging '91, San Jose,CA, edited by Bernice E. Rogowitz, Michael H. Brill, and Jan P. Allebach. SPIE, 1991. http://dx.doi.org/10.1117/12.44360.

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Chen, Kok, and Gabriel G. Marcu. "Time varying halftoning." In Electronic Imaging, edited by Reiner Eschbach and Gabriel G. Marcu. SPIE, 1999. http://dx.doi.org/10.1117/12.373428.

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Fung, Yik-Hing, and Yuk-Hee Chan. "Green noise video halftoning." In 2014 International Conference on Digital Signal Processing (DSP). IEEE, 2014. http://dx.doi.org/10.1109/icdsp.2014.6900807.

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Jagmohan, Ashish, Anshul Sehgal, and Narendra Ahuja. "Isotropic error diffusion halftoning." In Proceedings of ICASSP '02. IEEE, 2002. http://dx.doi.org/10.1109/icassp.2002.5745366.

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Jagmohan, Sehgal, and Ahuja. "Isotropic error diffusion halftoning." In IEEE International Conference on Acoustics Speech and Signal Processing ICASSP-02. IEEE, 2002. http://dx.doi.org/10.1109/icassp.2002.1004624.

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Reports on the topic "Halftoning"

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Mese, Murat, and P. P. Vaidyanathan. Image Halftoning and Inverse Halftoning for Optimized Dot Diffusion. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada349626.

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George, Nicholas, and David M. Berfanger. Halftoning and Image Processing Algorithms. Fort Belvoir, VA: Defense Technical Information Center, February 1999. http://dx.doi.org/10.21236/ada369915.

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Mese, Murat, and P. P. Vaidyanathan. Improved Dot Diffusion For Image Halftoning. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada368062.

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Mese, Murat, and P. P. Vaidyanathan. Image Halftoning Using Optimized Dot Diffusion. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada349631.

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