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Inverse color to black-and-white halftone conversion via dictionary learning and color mapping

Authors:

Chang-Hwan Son,

Hyunseung ChooAuthors Info & Claims

Information Sciences—Informatics and Computer Science, Intelligent Systems, Applications: An International Journal, Volume 299, Issue C

Pages 1 - 19

https://doi.org/10.1016/j.ins.2014.12.002

Published: 01 April 2015 Publication History

Abstract

This paper challenges the problem of estimating the original red-green-blue (RGB) image from a black-and-white (B&W) halftone image with homogeneously distributed dot patterns. To achieve this goal, training RGB images are converted into color-embedded gray images using the conventional reversible color to gray conversion method, and then converted into halftone images using error diffusion in order to produce the corresponding B&W halftone images. The proposed method is composed of two processing steps: (1) restoring the color-embedded gray image from an input B&W halftone image using a sparse linear representation between the image patch pairs obtained from the images and (2) restoring the original colors from the color-embedded gray image using the reversible color to gray conversion and linear color mapping methods. The proposed method successfully demonstrates the recovery of colors similar to the originals. The experimental results indicate that the proposed method outperforms the conventional methods. It is suggested that our method is not only successfully applied for the color recovery of the B&W halftone image, but that it can also be extended to various applications including color restoration of printed image, hardcopy data hiding, and halftone color compression.

References

[1]

M. Aharon, M. Elad, A. Bruckstein, K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation, IEEE Trans. Signal Process., 54 (2006) 4311-4322.

[2]

M. Anderson, R. Motta, S. Chandrasekar, M. Stokes, Proposal for a standard default color space for the internet - sRGB, in: Proc. 4th Color Imaging Conf., 1996, pp. 238-246.

[3]

R. Bala, R. Eschbach, Spatial color-to-grayscale transform preserving chrominance edge information, in: Proc. 12th Color Imaging Conf., 2004, pp. 82-86.

[4]

O. Bulan, G. Sharma, V. Monga, Orientation modulation for data hiding in clustered-dot halftone prints, IEEE Trans. Image Process., 19 (2010) 2070-2084.

Digital Library

[5]

A. Chatterjee, B. Tudu, K. Paul, Towards optimized binary pattern generation for grayscale digital halftoning: a binary particle swarm optimization (BPSO) approach, J. Vis. Commun. Image Represent., 23 (2012) 1245-1259.

Digital Library

[6]

M. Chaumont, W. Puech, Protecting the color information by hiding it, in: Recent Advances in Signal Processing, vol. 22, In-TECH, 2009.

[7]

I.J. Cox, J. Kilian, F.T. Leighton, T. Shamoon, Secure spread spectrum watermarking for multimedia, IEEE Trans. Image Process., 6 (1997) 1673-1687.

Digital Library

[8]

R.L. de Queiroz, Reversible color-to-gray mapping using subband domain texturization, Pattern Recogn. Lett., 31 (2010) 269-276.

Digital Library

[9]

R.L. de Queiroz, K.M. Braun, Color to gray and back: color embedding into textured gray images, IEEE Trans. Image Process., 15 (2006) 1464-1470.

Digital Library

[10]

J.-L. Dugelay, S. Roche, C. Rey, G. Doerr, Still-image watermarking robust to local geometric distortions, IEEE Trans. Image Process., 15 (2006) 2831-2842.

Digital Library

[11]

M. Elad, M. Aharon, Image denoising via sparse and redundant representation over learned dictionaries, IEEE Trans. Image Process., 15 (2006) 3735-3736.

[12]

M. Fairchild, Color Appearance Model, Wiley, 2005.

[13]

L. Feng, D. Cong, H. Shu, B. Liu, Adaptive halftone watermarking algorithm based on particle swarm optimization, J. Multimedia, 8 (2013) 183-190.

[14]

A. Foi, V. Katkovnik, K. Egiazarian, Point shape-adaptive DCT for high-quality denoising and deblocking of grayscale and color images, IEEE Trans. Image Process., 16 (2006) 1395-1411.

[15]

M. Fu, O. Au, Data hiding watermarking for halftone images, IEEE Trans. Image Process., 11 (2002) 477-484.

[16]

Y.-H. Fung, Y.-H. Chan, Optimizing the error diffusion filter for blue noise halftoning with multiscale error diffusion, IEEE Trans. Image Process., 22 (2013) 413-417.

Digital Library

[17]

R. Gonzales, R. Woods, Digital Image Processing, Prentice Hall, 2002.

[18]

A.A. Gooch, S.C. Olsen, J. Tumblin, B. Gooch, Color2gray: salience-preserving color removal, in: Proc. ACM SIGGRAPH, 2005, pp. 634-639.

[19]

M. Grundland, N.A. Dodgson, Decolorize: fast, contrast enhancing, color to grayscale conversion, Pattern Recogn., 40 (2007) 2891-2896.

Digital Library

[20]

J.-M. Guo, A new model-based digital halftoning and data hiding designed with LMS optimization, IEEE Trans. Multimedia, 9 (2007) 687-700.

Digital Library

[21]

J.-M. Guo, Watermarking in dithered halftone images with embeddable cells selection and inverse halftoning, Signal Process., 88 (2008) 1496-1510.

Digital Library

[22]

A. Hore, D. Ziou, Image quality metrics: PSNR vs. SSIM, in: Proc. Int. Conf. Pattern Recognition, 2010, pp. 23-26.

[23]

T. Horiuchi, F. Nohara, S. Tominaga, Accurate reversible color-to-gray mapping algorithm without distortion conditions, Pattern Recogn. Lett., 31 (2010) 2405-2414.

Digital Library

[24]

R. Irony, D. Cohen-Or, D. Lischinski, Colorization by example, in: Proc. Eurographics Symposium on Rendering, 2005, pp. 201-210.

[25]

H.R. Kang, Color Technology for Electronic Imaging Devices, SPIE Press, 1997.

[26]

H.B. Kekre, S.D. Thepade, R.N. Chaturvedi, Color to gray and back' using normalization of color components with Cosine, Haar and Walsh Wavelet, IOSR J. Comput. Eng., 10 (2013) 95-104.

[27]

J.-G. Kim, G. Kim, Design of optimal filters for error-feedback quantization of monochrome pictures, Inform. Sci., 39 (1986) 285-298.

Digital Library

[28]

K.-W. Ko, D.-C. Kim, W.-J. Kyung, Y.-H. Ha, Color embedding and recovery using wavelet packet transform with pseudorandomized saturation code, J. Imag. Sci. Technol., 55 (2011) 030501-1-030501-10.

[29]

K.-W. Ko, O.-S. Kwon, C.-H. Son, Y.-H. Ha, Color embedding and recovery based on wavelet packet transform, J. Imag. Sci. Technol., 52 (2008) 010501-1-010501-10.

[30]

J.-H. Kwon, C.-H. Son, Y.-H. Cho, Y.-H. Ha, Text-enhanced error diffusion using multiplicative parameters and error scaling factor, J. Imag. Sci. Technol., 50 (2006) 437-447.

[31]

C.-S. Lee, Y.-W. Park, S.-J. Cho, Y.-H. Ha, Gamut mapping algorithm using lightness mapping and multiple anchor points for linear tone and maximum chroma reproduction, J. Imag. Sci. Technol., 45 (2001) 209-223.

[32]

M.-Y. Lee, C.-H. Son, J.-M. Kim, C.-H. Lee, Y.-H. Ha, Illumination-level adaptive color reproduction method with lightness adaptation and flare compensation for mobile display, J. Imag. Sci. Technol., 51 (2007) 44-52.

[33]

T. Leung, J. Malik, Recognizing surfaces using three-dimensional textons, in: Proc. Int. Conf. Comput. Vis., 1999, pp. 1010-1017.

[34]

J. Lin, T. Horiuchi, K. Hirai, S. Tominaga, Color image recovery system from printed gray image, in: Proc. IEEE Southwest Symposium on Image Analysis and Interpretation, 2014, pp. 41-44.

[35]

M. Mese, P. Vaidyanathan, Look-up table (LUT) method for inverse halftoning, IEEE Trans. Image Process., 10 (2001) 1566-1578.

Digital Library

[36]

Y. Miyashita, M. Hasegawa, S. Kato, Y. Tanaka, Improved adaptive color embedding and recovery using DC level shifting, in: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2013, pp. 1588-1592.

[37]

R. Nasanen, Visibility of halftone dot textures, IEEE Trans. Syst., Man, Cybernet., smc-14 (1984) 920-924.

[38]

R. Neelamani, R. Nowak, R. Baraniuk, Model-based inverse halftoning with wavelet-vaguelette deconvolution, in: Proc. IEEE Int. Conf. Image Processing, 2000, pp. 973-976.

[39]

A. Piva, M. Barni, F. Bartolini, V. Cappellini, DCT-based watermark recovering without resorting to the uncorrupted original image, in: Proc. IEEE Int. Conf. Image Processing, 1997, pp. 520-523.

[40]

S. Pollard, R. Ulichney, M. Gaubatz, Recovering planar projections of printed clustered-dot halftones, in: Proc. IEEE Int. Conf. Image Processing, 2014, pp. 4226-4230.

[41]

J. Qin, N. Yung, Scene categorization via contextual visual words, Pattern Recogn., 43 (2010) 1874-1888.

Digital Library

[42]

M.A. Ruzon, S. Cohen, G. Wilensky, M. Newell, Fast and adaptive color-to-grayscale conversion, in: Proc. ACM SIGGRAPH Sketches, 2006, pp. 124-125.

[43]

C.-H. Son, H. Choo, Iterative inverse halftoning based on texture-enhancing deconvolution and error-compensating feedback, Signal Process., 93 (2013) 1126-1140.

Digital Library

[44]

C.-H. Son, H. Choo, Watermark detection from clustered halftone dots via learned dictionaries, Signal Process., 102 (2014) 77-84.

[45]

C.-H. Son, C.-H. Lee, K.-H. Park, Y.-H. Ha, Real-time color matching between camera and LCD based on 16-bit lookup table design in mobile phone, J. Imag. Sci. Technol., 51 (2007) 348-359.

[46]

C.-H. Son, H.-M. Park, A pair of noisy/blurry patches-based PSF estimation and channel-dependent deblurring, IEEE Trans. Consum. Electron, 57 (2011) 1791-1799.

[47]

H. Song, B. Huang, K. Zhang, H. Zhang, Spatio-spectral fusion of satellite images based on dictionary-pair learning, Inform. Fusion, 18 (2014) 148-160.

Digital Library

[48]

R. Stevenson, Inverse halftoning via MAP estimation, IEEE Trans. Image Process., 6 (1997) 574-583.

Digital Library

[49]

B. Sun, S. Li, J. Sun, Scanned image descreening with image redundancy and adaptive filtering, IEEE Trans. Image Process., 23 (2014) 3698-3710.

[50]

K. Uruma, K. Konishi, T. Takahashi, T. Furukawa, An image colorization algorithm using sparse optimization, in: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, 2013, pp. 1588-1592.

[51]

T. Welsh, M. Ashikhmin, K. Mueller, Transferring color to greyscale images, in: Proc. ACM SIGGRAPH, 2002, pp. 277-280.

[52]

Z.-Q. Wen, Y.-L. Lu, Z.-G. Zeng, W.-Q. Zhu, J.-H. Ai, Optimizing template for lookup-table inverse halftoning using elitist genetic algorithm, IEEE Signal Process. Lett., 22 (2015) 71-75.

[53]

J. Wright, A.Y. Yang, A. Ganesh, S. Sastry, Y. Ma, Robust face recognition via sparse representation, IEEE Trans. Pattern Anal. Mach. Intell., 31 (2009) 210-227.

Digital Library

[54]

Q. Zhang, J. Jia, 100+ times faster weighted median filter (WMF), in: Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2014, pp. 2830-2837.

Digital Library

Cited By

Wang X(2019)Probabilistic Neural Network for Reasons of the Low Quality LTE Networks ClassificationProceedings of the 2nd International Conference on Big Data Technologies10.1145/3358528.3358559(268-271)Online publication date: 28-Aug-2019
https://dl.acm.org/doi/10.1145/3358528.3358559
Xu ZChan Y(2018)Improving reversible color-to-grayscale conversion with halftoningImage Communication10.1016/j.image.2016.12.00552:C(111-123)Online publication date: 27-Dec-2018
https://dl.acm.org/doi/10.1016/j.image.2016.12.005
Su PTsai TChien Y(2018)Visual secret sharing in halftone images by multi-scale error diffusionMultimedia Tools and Applications10.1007/s11042-017-4861-077:10(12111-12138)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1007/s11042-017-4861-0
Show More Cited By

Inverse color to black-and-white halftone conversion via dictionary learning and color mapping
1. Computing methodologies
  1. Artificial intelligence
  2. Computer graphics

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Published In

cover image Information Sciences: an International Journal

Information Sciences: an International Journal Volume 299, Issue C

April 2015

433 pages

ISSN:0020-0255

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Copyright © Elsevier Inc.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 April 2015

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Cited By

Wang X(2019)Probabilistic Neural Network for Reasons of the Low Quality LTE Networks ClassificationProceedings of the 2nd International Conference on Big Data Technologies10.1145/3358528.3358559(268-271)Online publication date: 28-Aug-2019
https://dl.acm.org/doi/10.1145/3358528.3358559
Xu ZChan Y(2018)Improving reversible color-to-grayscale conversion with halftoningImage Communication10.1016/j.image.2016.12.00552:C(111-123)Online publication date: 27-Dec-2018
https://dl.acm.org/doi/10.1016/j.image.2016.12.005
Su PTsai TChien Y(2018)Visual secret sharing in halftone images by multi-scale error diffusionMultimedia Tools and Applications10.1007/s11042-017-4861-077:10(12111-12138)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1007/s11042-017-4861-0
Zhang FLi ZQu XZhang X(2018)Inverse Halftoning Algorithm Based on SLIC Superpixels and DBSCAN ClusteringIntelligent Computing Methodologies10.1007/978-3-319-95957-3_49(466-471)Online publication date: 15-Aug-2018
https://dl.acm.org/doi/10.1007/978-3-319-95957-3_49
Gorbachev VKaynarova EMetelev IYakovleva E(2017)On Color-to-Gray Transformation for Distributing Color Digital ImagesProceedings of the 20th Conference of Open Innovations Association FRUCT10.23919/FRUCT.2017.8071295(77-82)Online publication date: 10-Apr-2017
https://dl.acm.org/doi/10.23919/FRUCT.2017.8071295

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