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

LDPC를 이용한 예측 기반 워터마킹 알고리듬

  • 임재혁 (연세대학교 전기전자공학부) ;
  • 원치선 (동국대학교 전자공학과)
  • Published : 2007.01.25

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.

본 논문에서는 워터마크 예측과 LDPC 코드를 이용하여 워터마크의 성능을 향상시키는 알고리듬을 제안한다. 워터마크 추출의 경우 삽입된 워터마크의 파워(power)가 원본 영상의 파워에 비해 아주 작기 때문에 워터마크의 추출 성능을 높이기 위해서는 워터마크의 예측이 필수적이다. 본 논문에서는 웨이블릿 영역에서 잡음 제거 필터를 사용하여 워터마크의 예측을 수행하였다. 이렇게 예측된 워터마크에 에러가 발생할 경우 LDPC 코드를 사용하여 수정하였다. 에러 수정 시 삽입된 워터마크의 통계적인 특성을 사용하여 기존의 LDPC 코드의 성능보다 우수한 실험 결과를 도출하였다.

Keywords

References

  1. M. Costa, 'Writing on Dirty Paper,' IEEE Trans. Inform. Theory, vol. 29, pp. 439-441. May 1983 https://doi.org/10.1109/TIT.1983.1056659
  2. 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
  3. 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 https://doi.org/10.1109/83.862630
  4. R. G. Gallager, 'Low Density Parity Check Codes,' IRE Trans. Info. Theory, IT-8:21-28, Jan. 1962
  5. 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
  6. John G. Proakis, 'Digital Communication Chap. 1,' Forth edition, McGraw-Hill Series in Electrical and Computer Engineering, 2001
  7. 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
  8. J. K. Su and B. Girod, 'Power-Spectrum Condition for Energy-Efficient Watermarking,' Proc. IEEE ICIP, Oct. 1999 https://doi.org/10.1109/ICIP.1999.821618
  9. 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 https://doi.org/10.1109/18.910578
  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. 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 https://doi.org/10.1109/18.910577
  12. 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 https://doi.org/10.1109/18.910572
  13. 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
  14. M. Kutter, 'Digital Image Watermarking: Hiding Information in Images,' Ph. D Thesis, EPFL, Lausanne, Switzerland, Aug. 1999