IEICE TRANSACTIONS on Fundamentals
Content-Adaptive Robust Image Watermarking with Posterior HMM-Based Detector
Summary :
Robustness and invisibility are two contrary constraints for robust invisible watermarking. Instead of the conventional strategy with human visual system (HVS) model, this paper presents a content-adaptive approach to further optimize the constraint between them. To reach this target, the entropy-based and integrated HVS (IHVS) based measures are constructed so as to adaptively choose the suitable components for watermark insertion and detection. Such a kind of scheme potentially gives rise to synchronization problem between the encoder and decoder under the framework of blind watermarking, which is then solved by incorporating the repeat-accumulate (RA) code with erasure and error correction. Moreover, a new hidden Markov model (HMM) based detector in wavelet domain is introduced to reduce the computation complexity and is further developed into a posterior one to avoid the transmission of HMM parameters with only a little sacrifice of detection performance. Experimental results show that the proposed algorithm can obtain considerable improvement in robustness performance with the same distortion as the traditional one.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.8 pp.1953-1960
- Publication Date
- 2008/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.8.1953
- Type of Manuscript
- Special Section PAPER (Special Section on Signal Processing)
- Category
Authors
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Chuntao WANG, Jiangqun NI, Rongyue ZHANG, Goo-Rak KWON, Sung-Jea KO, "Content-Adaptive Robust Image Watermarking with Posterior HMM-Based Detector" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 8, pp. 1953-1960, August 2008, doi: 10.1093/ietfec/e91-a.8.1953.
Abstract: Robustness and invisibility are two contrary constraints for robust invisible watermarking. Instead of the conventional strategy with human visual system (HVS) model, this paper presents a content-adaptive approach to further optimize the constraint between them. To reach this target, the entropy-based and integrated HVS (IHVS) based measures are constructed so as to adaptively choose the suitable components for watermark insertion and detection. Such a kind of scheme potentially gives rise to synchronization problem between the encoder and decoder under the framework of blind watermarking, which is then solved by incorporating the repeat-accumulate (RA) code with erasure and error correction. Moreover, a new hidden Markov model (HMM) based detector in wavelet domain is introduced to reduce the computation complexity and is further developed into a posterior one to avoid the transmission of HMM parameters with only a little sacrifice of detection performance. Experimental results show that the proposed algorithm can obtain considerable improvement in robustness performance with the same distortion as the traditional one.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.8.1953/_p
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@ARTICLE{e91-a_8_1953,
author={Chuntao WANG, Jiangqun NI, Rongyue ZHANG, Goo-Rak KWON, Sung-Jea KO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Content-Adaptive Robust Image Watermarking with Posterior HMM-Based Detector},
year={2008},
volume={E91-A},
number={8},
pages={1953-1960},
abstract={Robustness and invisibility are two contrary constraints for robust invisible watermarking. Instead of the conventional strategy with human visual system (HVS) model, this paper presents a content-adaptive approach to further optimize the constraint between them. To reach this target, the entropy-based and integrated HVS (IHVS) based measures are constructed so as to adaptively choose the suitable components for watermark insertion and detection. Such a kind of scheme potentially gives rise to synchronization problem between the encoder and decoder under the framework of blind watermarking, which is then solved by incorporating the repeat-accumulate (RA) code with erasure and error correction. Moreover, a new hidden Markov model (HMM) based detector in wavelet domain is introduced to reduce the computation complexity and is further developed into a posterior one to avoid the transmission of HMM parameters with only a little sacrifice of detection performance. Experimental results show that the proposed algorithm can obtain considerable improvement in robustness performance with the same distortion as the traditional one.},
keywords={},
doi={10.1093/ietfec/e91-a.8.1953},
ISSN={1745-1337},
month={August},}
Copy
TY - JOUR
TI - Content-Adaptive Robust Image Watermarking with Posterior HMM-Based Detector
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1953
EP - 1960
AU - Chuntao WANG
AU - Jiangqun NI
AU - Rongyue ZHANG
AU - Goo-Rak KWON
AU - Sung-Jea KO
PY - 2008
DO - 10.1093/ietfec/e91-a.8.1953
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2008
AB - Robustness and invisibility are two contrary constraints for robust invisible watermarking. Instead of the conventional strategy with human visual system (HVS) model, this paper presents a content-adaptive approach to further optimize the constraint between them. To reach this target, the entropy-based and integrated HVS (IHVS) based measures are constructed so as to adaptively choose the suitable components for watermark insertion and detection. Such a kind of scheme potentially gives rise to synchronization problem between the encoder and decoder under the framework of blind watermarking, which is then solved by incorporating the repeat-accumulate (RA) code with erasure and error correction. Moreover, a new hidden Markov model (HMM) based detector in wavelet domain is introduced to reduce the computation complexity and is further developed into a posterior one to avoid the transmission of HMM parameters with only a little sacrifice of detection performance. Experimental results show that the proposed algorithm can obtain considerable improvement in robustness performance with the same distortion as the traditional one.
ER -
English
