Wavelet-based Digital Watermarking Using Human Visual System and Subband Adaptive Threshold

인간 시각 시스템과 부대역 적응적 문턱값을 이용한 웨이브릿 기반의 디지털 워터마킹

  • Ha, Min-Seong (School of Electronic & Electrical Engineering, Kyungpook National University) ;
  • Gwon, Seong-Gon (School of Electronic & Electrical Engineering, Kyungpook National University) ;
  • Lee, Jong-Won (School of Electronic & Electrical Engineering, Kyungpook National University) ;
  • Ban, Seong-Won (School of Electronic & Electrical Engineering, Kyungpook National University) ;
  • Lee, Seung-Jin (School of Electronic & Electrical Engineering, Kyungpook National University) ;
  • Gwon, Gi-Yong ;
  • Lee, Geon-Il (School of Electronic & Electrical Engineering, Kyungpook National University)
  • 하민성 (경북대학교 전자전기공학부) ;
  • 권성곤 (경북대학교 전자전기공학부) ;
  • 이종원 (경북대학교 전자전기공학부) ;
  • 반성원 (경북대학교 전자전기공학부) ;
  • 이승진 (경북대학교 전자전기공학부) ;
  • 권기용 (부산외국어대학교 전자공학과) ;
  • 이건일 (경북대학교 전자전기공학부)
  • Published : 2000.11.01

Abstract

In this paper, we proposed a wavelet-based digital watermarking algorithm using human visual system and subband-adaptive threshold. After the original image is transformed by discrete wavelet transform, the perceptually significant coefficients of the each subband excluding the lowest level subbands are utilized to embed the watermark. To select perceptually significant coefficients for each subband, we use subband-adaptive threshold. For the selected coefficients in the high frequency subbands, the watermark is embedded using HVS. For those of the baseband, the watermark is embedded by conventional embedding method. We tested the performance of the proposed algorithm compared with conventional watermarking algorithm by computer simulation. The experimental results show that the proposed watermarking algorithm is less visible to human eyes and more robust to image compressions, image processings, and geometric transformations than the conventional algorithm.

본 논문에서는 인간 시각 시스템과 부대역 적응적 문턱값을 이용한 웨이브릿 기반의 디지털 워터마킹 알고리듬을 제안하였다. 이 알고리듬에서는 웨이브릿 변환을 이용하여 영상을 3-레벨로 분해한 후, 가장 낮은 레벨에 속한 최고주파 부대역들을 제외한 모든 부대역들에 대하여 각 부대역별로 적응적인 문턱값을 이용하여 시각적으로 중요한 웨이브릿 계수를 선택한다. 고주파 부대역에 속한 시각적으로 중요한 웨이브릿 계수들은 각 계수들에 대한 인간 시각 시스템을 고려하여 시각적으로 보이지 않는 크기로 워터마크를 삽입한다. 기저대역에 속한 계수들은 화질 열화가 일어나지 않는 범위로 워터마크를 삽입한다. 본 워터마킹 알고리듬의 성능 평가를 위한 모의실험에서 이 알고리듬이 기존의 알고리듬보다 비가시성과 견고성에서 모두 우수함을 확인하였다.

Keywords

References

  1. R. G. van Schyndel, A. Z. Tirkel, and C. F. Osborne, A DIGITAL WATERMARK, IEEE Int. Conf. on Image Processing, Vol. 2, pp. 86-90, 1994
  2. Joannis Pitas, A Method for Watermark Casting on Digital Images, IEEE Trans. on Circuits and System for Video Technology, Vol. 8, No. 6, pp. 775-780, Oct. 1998 https://doi.org/10.1109/76.728421
  3. I. Cox, J. Kilian, T. Leighton and T. Shamoon, 'Secure Spread Spectrum Watermarking for Multimedia,' IEEE Transactions on Image Processing, Vol. 6, pp. 1673-1687, Dec. 1997 https://doi.org/10.1109/83.650120
  4. A. Piva, M. Bami, F. Bartolini, and V. Cappellini, DCT-base Watermark Recovering without Resorting to the Uncorrupted Original Image, IEEE Int. Conf. on Image Processing, Vol. 1, pp. 520-523, 1997 https://doi.org/10.1109/ICIP.1997.647964
  5. M. D. Swanson, B. Zhu, and A. H. Tewlik, TRANSPARENT ROBUST IMAGE WATERMARKING, IEEE Int. Conf. on Image Processing, Vol. 1, pp. 211-214, 1996 https://doi.org/10.1109/ICIP.1996.560421
  6. J. J. K. Ruanaidh, W. J. Dowing, and F. M. Boland PHASE WATERMARKING OF DIGITAL IMAGES, IEEE Int. Conf. on Image Processing, Vol. 3, pp. 239-242, 1996 https://doi.org/10.1109/ICIP.1996.560428
  7. X. G. Xia and C. G. Boncelet and G. R. Arce, 'A Multiresolution Watermark for Digital Images,' Proc. of IEEE ICIP, Vol.3, pp.548-551, 1997 https://doi.org/10.1109/ICIP.1997.647971
  8. D. Kundar and D. Hatzinakos, A Robust Digital Image Watermarking Method using Wavelet-Based Fusion, IEEE Int. Conf. on Image Processing, Vol. 1, pp. 544-547, 1997 https://doi.org/10.1109/ICIP.1997.647970
  9. M. Barni, F. Bartolini, V. Cappellini, A. Lippi, and A. Piva, A DWT-based technique for spatio frequency masking of digital signatures, SPIE Conf. on Visual Comm. and Image Processing, Vol. 3657, pp. 31-39, 1999 https://doi.org/10.1117/12.344689
  10. A. S. Lewis and G. Knowles, 'Image compression using the 2-D wavelet transform,' IEEE Trans. Image Processing, Vol.1, pp.244-250, Apr., 1992 https://doi.org/10.1109/83.136601