Abstract
This paper proposes a novel adaptive filtering technique to achieve high-quality image enhancement when the image possesses the artifact of moiré pattern during the reproduction by different computer peripherals such as color copiers, or scanners plus printers.
Commercial magazine images are halftoned images. Unacceptable noises and moiré distortion may occur when halftone images are copied (i.e., scanned and printed). In this paper, we analyze the formation of moiré patterns in both the frequency and spatial domain. Basically moiré noise often appears due to the aliased frequency when a halftone image is scanned. Based on the analysis of the scanned halftone image, we develop an adaptive filter to suppress the moiré artifacts and produce the high-quality image reproduction. The adaptive filter consists of modules of anti-aliased filter and image enhance filter: the anti-aliased filter is applied to cancel aliased low frequency components (moiré distortion); the image enhance filter is applied to sharpen image edges. It depends on the information provided by an image classification module to decide either the anti-aliased or image enhance module should be applied. The classification module is developed based on a set of pyramid images to determine an edge is either a global true edge (for sharpening enhancement) or a local halftone’s micro-structural edge (for moiré reduction). Depending on the information from the classification module, the adaptive filter technique then applies the anti-aliased filter to the halftone micro-structured edge or the enhanced filter to the image global edge correctly and efficiently, and therefore both the moiré reduction and image enhancement can be achieved simultaneously. Experimental results show the outstanding effectiveness of the presented technique for high-quality magazine image reproduction.
Similar content being viewed by others
References
J.C. Stoffel and J.F. Moreland, “A Survey of Electronic Techniques for Pictorial Image Reproduction,” IEEE Trans. On Commun., vol. COM-29, no. 12, 1981.
R. Ulchney, Digital Halftoning, Cambridge, MA; The MIT Press, 1987.
Henry R. Kang, Digital Color Halftoning, Piscataway, NJ: IEEE Press, 1999.
O. Bryngdahl, “Moiré: Formation and interpretation,” J. Opt. Soc. Amer. vol. 64, 1974, pp. 1287–1294.
A. Glassner, “Inside Moiré Patterns,” IEEE Computer Graphics Application, vol. 17, 1997, pp. 97–101.
J.F. Blinn, “Jim Blinn’s Corner: What We Need Around Here is Morealiasing,” IEEE Computer Graphics Application, vol. 9, 1989, pp. 75–79.
J.F. Blinn, “Jim Blinn’s Corner: Return of the Jaggy,” IEEE computer Graphics Application, vol. 9, 1989, pp. 82–88.
I. Amidror, The Theory of the Moiré phenomenon,” Computational Imaging and Vision, vol. 15, Kluwer Academic, Dordrecht, 2000.
D.M. Meadows, W.O. Johnson, and J.B. Allen, “Generation of Surface Contours by Moiré Patterns,” Applied Optics, vol. 9, no. 4, April 1970, pp. 942–947.
P. Pochec, “Moire Patterns in Disparity Measurement,” IEEE Proceedings. Communications, Computers, and Signal Processing, pp. 420–422, 1995.
A. Tran, J. Lee, K. Zhang, and Y. Lo, “Ultrafine Motion Detection of Micromechanical Structures Using Optical Moiré Patterns,” IEEE Photonics Technology Letters, vol. 8, no. 8, 1996, pp. 1058–1060.
J. Shu, R. Springer, and C. Yeh, “Moiré Factors and Visibility in Scanned and Printed Halftone images,” Optical Engineering, vol. 28, no. 7, 1989, pp. 805–812.
A. Rosenfeld and A.C. Kak, Digital Picture Processing, Chapter 4, 2nd ed., New York: Academic Press, 1981.
T.S. Huang, “Digital Transmission of Halftone Pictures,” Computer Graphics and Image Processing, vol. 3, 1974, pp. 195–202.
A. Steinbach and K.Y. Wong, “An Understanding of Moiré Patterns in the Reproduction of Halftone Images,” IEEE Computer Society Conference on Pattern Recognition and Image Processing, 1979, pp. 545–552,
X. Liu and R. Ehrich, “Analysis of Moire Patterns in Non-Uniformly Sampled Halftones,” in Proceedings 3rd IEEE Workshop on Applications of Computer Vision, 1996, pp. 208–213.
P.G. Roetling, “Halftone Method with Edge Enhancement and Moiré Suppression,” J. Opt. Soc. Am., vol. 10, 1976, pp. 985–989.
Joseph Shu, Jamie Li, and Andrei Pascovici, “Multiple Layer Screening for Reducing Moire Patterning and Ink Bleeding,” IEEE International Conference on Image Processing,Oct. 26–29, Santa Barbara, CA, 1997.
Dimitri Van De Ville, K. Denecker, W. Philips, and I. Lemahieu, “Nonlinear Resampling for Edge Preserving Moiré Suppression,” Journal of Electronic Imaging, vol. 9, no. 4, 2000, pp. 534–547.
J. Shu, “Reproduction of Halftone Original with Moiré Reduction and Tone Adjustment” US Patent no. 4,942,480 July 17, 1990.
D. Kermisch and P.G. Roetling, “Fourier Spectrum of Halftone Images,” J. Opt. Soc. Am., vol. 65, 1975, pp. 716–723.
J.P. Allebach and B. Liu, “Analysis of Halftone Dot Profile and Aliasing in the Discrete Binary Representation on Images,” J. Opt. Soc. Am., vol. 67, 1977, pp. 1147–1154.
A.V. Oppenheim and R.W. Schafer, Discrete-Time Signal Processing, Prentice-Hall, 1989.
M. Antonini, M. Barlaud, P. Mathieu, and I. Daubechies, “Image Coding Using Wavelet Transform,” IEEE Trans. Image Processing, vol. 1, 1992, pp. 204–220.
A. Said and W. Pearlman, “A New Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees,” IEEE Trans. Circuits and Systems for Video Technology, vol. 6, 1996, pp. 243–150.
J. Shu, A. Bhattacharjya, and Tsung-Nan Lin, “Reduction of Moire in Screened Images Using Hierarchical Edge Detection and Adaptive-Length Averaging Filters,” US Patent 6,233,060, May 15, 2001.
Author information
Authors and Affiliations
Corresponding author
Additional information
Joseph Shu was born in Taiwan, Republic of China in 1954. He received his B.S. degree from Communication Engineering department, National Chiao-Tung University, Taiwan, R.O.C. in 1978, M.S. degree in 1984 and Ph.D. degree in 1986 both in Electric, Computer, and Systems Engineering department, Rensselaer Polytechnic Institute, Troy, New York. From 1986 to 1990, Dr. Shu worked for NYNEX Corporation. From 1990 to 1991, he worked in Hewlett-Packard Labs. Since 1991, he has been working for Epson. He is now a consultant scientist for Epson Palo Alto Lab. He has 35 U.S. patents. He has published over 25 technical papers in image segmentation, enhancement, restoration, analysis, moire reduction, pattern recognition, color processing and halftoning.
Tsung-Nan Lin received B.S. degree in electrical engineering from National Taiwan University, Taiwan, R.O.C. in 1989, and M.A. and Ph.D. degrees from Princeton University in 1993 and 1996, respectively, both in electrical engineering department. He was a Teaching Assistant with the Department of Electrical Engineering from 1991 to 1992. Hewas with NEC Research Institute as a Research Assistant from 1992 to 1996. He has been with EPSON R&D Inc and EMC. Since Feb. 2002, he has been with Department of Electrical Engineering and Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan. Tsung-Nan Lin is a member of PHI TAUPHI scholastic honor society and a senior member of IEEE.
Rights and permissions
About this article
Cite this article
Lin, T.N., Shu, J. Adaptive-Hierarchical-Filtering Technique for High-Quality Magazine Image Reproduction. J VLSI Sign Process Syst Sign Image Video Technol 39, 237–247 (2005). https://doi.org/10.1007/s11265-005-4842-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11265-005-4842-9