Abstract:
This letter proposes a robust spread spectrum image watermark detection on compressed sensing (CS) measurements degraded by both multiplicative and additive noise. Waterm...Show MoreMetadata
Abstract:
This letter proposes a robust spread spectrum image watermark detection on compressed sensing (CS) measurements degraded by both multiplicative and additive noise. Watermark detection threshold is calculated first using log-likelihood ratio model. Distortion minimization problem is then formulated in terms of watermark embedding strength and the number of CS measurements under the constraint of detector reliability. A large set of simulation results show high detection probability with low false rate at low watermark power.
Published in: IEEE Sensors Letters ( Volume: 1, Issue: 5, October 2017)
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- IEEE Keywords
- Index Terms
- Spread Spectrum ,
- Watermark Detection ,
- Simulation Results ,
- Likelihood Ratio Test ,
- Detection Threshold ,
- Additive Noise ,
- Detection Probability ,
- Multiplicative Noise ,
- Low False Rate ,
- Digital Watermarking ,
- False Discovery Rate ,
- Optimization Problem ,
- Gaussian Noise ,
- Image Reconstruction ,
- Wavelet Transform ,
- Additive Gaussian ,
- Additive Gaussian Noise ,
- Discrete Cosine Transform ,
- Number Of Strength ,
- Total Covariance
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Spread Spectrum ,
- Watermark Detection ,
- Simulation Results ,
- Likelihood Ratio Test ,
- Detection Threshold ,
- Additive Noise ,
- Detection Probability ,
- Multiplicative Noise ,
- Low False Rate ,
- Digital Watermarking ,
- False Discovery Rate ,
- Optimization Problem ,
- Gaussian Noise ,
- Image Reconstruction ,
- Wavelet Transform ,
- Additive Gaussian ,
- Additive Gaussian Noise ,
- Discrete Cosine Transform ,
- Number Of Strength ,
- Total Covariance
- Author Keywords