other · UCL Discovery (University College London) · 2007

Trellis coded modulation to improve dirty paper trellis watermarking

Chin, KW, Doërr, G, Cox, I

Cited by 1Abstract and details only

Abstract

Lattice codes and quantization-based techniques have received considerable attention as a method of digital watermarking with side information. However, these algorithms are also recognized to be highly sensitive to common signal processing primitives such as valuemetric scaling, e.g. changes in volume of a song, or re-quantization, e.g. JPEG compression. Hence, it is reasonable to investigate alternative codes which may offer the potential for superior performance. In previous work, we designed a new class of codes, called dirty paper trellis codes (DPTC), which are by construction immune to valuemetric scaling. Although DPTC have shown themselves to be resistant to certain classes attacks, the trellises were generated randomly, thus leading to suboptimal codes. In this paper, Ungerboeck's work on trellis coded modulation (TCM) is exploited to significantly improve the performance of the DPTC. Experimental results show that the resulting trellises significantly outperform the original design. © 2007 SPIE-IS&T.

Cite this paper

APA 7

Chin, K., Doërr, G., & Cox, I. (2007). Trellis coded modulation to improve dirty paper trellis watermarking. UCL Discovery (University College London).

MLA 9

Chin, KW, et al. “Trellis coded modulation to improve dirty paper trellis watermarking.” UCL Discovery (University College London), 2007.

Chicago

Chin, KW, G Doërr, and I Cox. 2007. “Trellis coded modulation to improve dirty paper trellis watermarking.” UCL Discovery (University College London).

Harvard

Chin, K., Doërr, G. and Cox, I. (2007) ‘Trellis coded modulation to improve dirty paper trellis watermarking’, UCL Discovery (University College London).

BibTeX

@misc{chin2007trellis,
  title = {{Trellis coded modulation to improve dirty paper trellis watermarking}},
  author = {Chin, KW and Doërr, G and Cox, I},
  journal = {UCL Discovery (University College London)},
  year = {2007}
}

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