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Estimation-based Watermarking Algorithm with Low Density Parity Check (LDPC) Codes  

Lim, Jae-Hyuck (Yonsei University Electrical & Electronic Eng.)
Won, Chee-Sun (Dongguk University Electronic Eng.)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.44, no.1, 2007 , pp. 76-84 More about this Journal
Abstract
The goal of this paper is to improve the watermarking performance using the following two methods; watermark estimation and low density parity check (LDPC) codes. For a blind watermark decoding, the power of a host image, which is hundreds times greater than the watermark power, is the main noise source. Therefore, a technique that can reduce the effect of the power of the host image to the detector is required. To this end, we need to estimate watermark from the watermarked image. In this paper, the watermark estimation is done by an adaptive estimation method with the generalized Gaussian distribution modeling of sub-band coefficients in the wavelet domain. Since the watermark capacity as well as the error rate can be improved by adopting optimum decoding principles and error correcting codes (ECC), we employ the LDPC codes for the decoding of the estimated watermark. Also, in LDPC codes, the knowledge about the noise power can improve the error correction capability. Simulation results demonstrate the superior performance of the proposed algorithm comparing to LDPC decoding with other estimation-based watermarking algorithms.
Keywords
Watermark Estimation; LDPC Codes; Wavelet Transform; De-noising Filter;
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  • Reference
1 M. Kutter, 'Digital Image Watermarking: Hiding Information in Images,' Ph. D Thesis, EPFL, Lausanne, Switzerland, Aug. 1999
2 R. G. Gallager, 'Low Density Parity Check Codes,' IRE Trans. Info. Theory, IT-8:21-28, Jan. 1962
3 David J. C. Mackay and Christopher P. Hesketh, 'Performance of Low Density Parity Check Codes as a Function of Actual and Assumed Noise Levels,' IEEE Trans. on communication, July, 15, 1998
4 John G. Proakis, 'Digital Communication Chap. 1,' Forth edition, McGraw-Hill Series in Electrical and Computer Engineering, 2001
5 S. Voloshynovskiy, A. Herrigel, N. Baumgartner and T. Pun, 'A Stochastic Approach to Content Adaptive Digital Image Watermarking,' International Workshop on Information Hiding, Dresden, Germany, LNCS, Andreas Pfitzmann Ed., pp. 211-236, Sep. 29-Oct. 1, 1999
6 J. K. Su and B. Girod, 'Power-Spectrum Condition for Energy-Efficient Watermarking,' Proc. IEEE ICIP, Oct. 1999   DOI
7 T. Richardson, A. Shokrollahi and R. Urbanke, 'Design of Capacity Approaching Irregular Low Density Parity Check Codes,' IEEE Trans. Inform. Theory, vol. 47, pp. 619-637, Feb. 2001   DOI   ScienceOn
8 M. Costa, 'Writing on Dirty Paper,' IEEE Trans. Inform. Theory, vol. 29, pp. 439-441. May 1983   DOI
9 T. Richarson and R. Urbanke, 'The Capacity of Low Density Parity Check Codes under Message Passing Decoding,' IEEE Trans. Inform. Theory, vol. 47, pp. 599-618, Feb. 2001   DOI   ScienceOn
10 N. Wiberg, H. A. Loeliger and R. Kotter, 'codes and Iterative Decoding on General Graghs,' IEEE Trans. Inform. Theory, vol. IT-27, pp. 533-547, Sept. 1981
11 F. R. Kschischang, B. J. Frey, and H. A. Loeliger, 'Factor Graphs and the Sum Product Algorithm,' IEEE Trans. Inform. Theory, vol. 47, pp. 498-519, Feb. 2001   DOI   ScienceOn
12 J. H. Lim and C. S. Won, 'Object-based Watermarking Algorithm for AdaptiveTranscoding of Multiple Objects,' First International Workshop, IWDW 2002, Seoul,Korea, Nov. 2002
13 Joachim J. Eggers, Jonathan K. Su and Bernd Girod, 'Performance of a Practical Blind Watermarking Scheme,' Electronic Imaging 2001, San Jose, CA. USA, Jan. 2001
14 S. Grace Chang, Bin Yu and M. Vattereli, 'Spatially Adaptive Wavelet Thresholding with Context Modeling for Image De-noising,' IEEE Trans. Image Processing, vol. 9, pp. 1522-1530, Sep. 2000   DOI   ScienceOn