Design an aperiodic stochastic resonance signal processor for digital watermarking

Shuifa SUN, Bangjun LEI, Sheng ZHENG, Sam KWONG, Xuejun ZHOU

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review


In this paper, we propose an aperiodic stochastic resonance (ASR) signal processor for communication systems based on a bi-stable mechanism. This processor can detect base-band binary pulse amplitude modulation (PAM) signals. In this processor related parameters can be adjusted. The adjustment mechanism is explained from the perspective of the conventional noise-induced nonlinear signal processing. To demonstrate this processors usability, based on it we implemented a digital image watermarking algorithm in the discrete cosine transform (DCT) domain. In this algorithm, the watermark and the DCT alternating current (ac) coefficients of the image are viewed as the input signal and the channel noise, respectively. This phenomenon that the detection bit error ratio (BER) of the system suffering from certain attacks is lower than that of the system not suffering from any attack is systematically analyzed. © 2008 Springer Berlin Heidelberg.
Original languageEnglish
Title of host publicationDigital Watermarking: 6th International Workshop, IWDW 2007 Guangzhou, China, December 3-5, 2007 Proceedings
EditorsYun Q. SHI, Hyoung-Joong KIM, Stefan KATZENBEISSER
PublisherSpringer Berlin Heidelberg
Number of pages15
ISBN (Electronic)9783540922384
ISBN (Print)9783540922377
Publication statusPublished - 2008
Externally publishedYes
Event6th International Workshop on Digital Watermarking - Guangzhou, China
Duration: 3 Dec 20075 Dec 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Workshop6th International Workshop on Digital Watermarking
Abbreviated titleIWDW 2007


  • Digital watermarking
  • Signal processing
  • Stochastic resonance


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