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Spread Spectrum Watermark Design under Noisy Compressive Sampling

Published on March 2013 by Anirban Bose, Santi P. Maity
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International Conference on Computing, Communication and Sensor Network
Foundation of Computer Science USA
CCSN2012 - Number 2
March 2013
Authors: Anirban Bose, Santi P. Maity
b365b52b-4c27-476f-9e44-14078f81f960

Anirban Bose, Santi P. Maity . Spread Spectrum Watermark Design under Noisy Compressive Sampling. International Conference on Computing, Communication and Sensor Network. CCSN2012, 2 (March 2013), 36-41.

@article{
author = { Anirban Bose, Santi P. Maity },
title = { Spread Spectrum Watermark Design under Noisy Compressive Sampling },
journal = { International Conference on Computing, Communication and Sensor Network },
issue_date = { March 2013 },
volume = { CCSN2012 },
number = { 2 },
month = { March },
year = { 2013 },
issn = 0975-8887,
pages = { 36-41 },
numpages = 6,
url = { /specialissues/ccsn2012/number2/10859-1022/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 International Conference on Computing, Communication and Sensor Network
%A Anirban Bose
%A Santi P. Maity
%T Spread Spectrum Watermark Design under Noisy Compressive Sampling
%J International Conference on Computing, Communication and Sensor Network
%@ 0975-8887
%V CCSN2012
%N 2
%P 36-41
%D 2013
%I International Journal of Computer Applications
Abstract

This paper proposes an algorithm for spread spectrum watermark design under compressive sampling (CS) attack using hybridization of genetic algorithm (GA) and neural network. In watermarking application, CS may be viewed as a typical fading-like attack operation on the watermarked image. GA is used to determine the watermark strength taking into consideration of both robustness and imperceptibility in the paradigm of CS with additive white Gaussian noise (AWGN) attack channel. Then NN assisted improved detector is developed to classify two image classes i. e. watermarked and non-watermarked one. Simulation results demonstrate the effectiveness of the proposed method.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Spread Spectrum Watermark Compressive Sampling Genetic Algorithms Neural Network