Suprathreshold stochastic resonance and maximizing network for watermark detection

22 February 2012 Suprathreshold stochastic resonance and maximizing network for watermark detection

Rajib K. Jha, Bhupendra Gupta, Deepak Mishra, Prabir K. Biswas

Author Affiliations +

Journal of Electronic Imaging, Vol. 21, Issue 1, 013001 (February 2012). https://doi.org/10.1117/1.JEI.21.1.013001

Abstract

We propose a novel method that improves watermark detection performance, based on suprathreshold stochastic resonance (SSR) with a maximizing network. The detection performance is measured in terms of correlation. The proposed method has been tested on different gray-scale images, and we found that an original image is not required for watermark detection, so this method is blind. We improved the correlation between an original watermark and the SSR with maximizing network-based discrete wavelet transform coefficients of the watermarked image. Our experimental results have been compared with the different existing techniques and were found superior in terms of correlation and ratio of correlation to threshold.

Citation Download Citation

Rajib K. Jha, Bhupendra Gupta, Deepak Mishra, and Prabir K. Biswas "Suprathreshold stochastic resonance and maximizing network for watermark detection," Journal of Electronic Imaging 21(1), 013001 (22 February 2012). https://doi.org/10.1117/1.JEI.21.1.013001

Published: 22 February 2012

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE