Blind image watermark detection algorithm based on discrete shearlet transform using statistical decision theory
Journal article
Authors | Ahmaderaghi, Baharak, Kurugollu, Fatih, Rincon, Jesus Martinez Del and Bouridane, Ahmed |
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Abstract | Blind watermarking targets the challenging recovery of the watermark when the host is not available during the detection stage.This paper proposes Discrete Shearlet Transform (DST) as a new embedding domain for blind image watermarking. Our novel DST blind watermark detection system uses a non-additive scheme based on the statistical decision theory. It first computes the Probability Density Function (PDF) of the DST coefficients modelled as a Laplacian distribution. The resulting likelihood ratio is compared with a decision threshold calculated using Neyman-Pearson criterion to minimise the missed detection subject to a fixed false alarm probability. Our method is evaluated in terms of imperceptibility, robustness and payload against different attacks (Gaussian noise, Blurring, Cropping, Compression and Rotation) using 30 standard grayscale images covering different characteristics (smooth, more complex with a lot of edges and high detail textured regions). The proposed method shows greater windowing flexibility with more sensitive to directional and anisotropic features when compared against Discrete Wavelet and Contourlets. |
Keywords | Digital image watermarking; Frequency domain; DST; Discrete Wavelet Transform; Contourlet Transform; Laplacian distribution |
Year | 2018 |
Journal | IEEE Transactions on Computational Imaging |
Publisher | IEEE |
ISSN | 2333-9403 |
2334-0118 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TCI.2018.2794065 |
Web address (URL) | http://hdl.handle.net/10545/623626 |
hdl:10545/623626 | |
Publication dates | 15 Jan 2018 |
Publication process dates | |
Deposited | 20 Mar 2019, 11:49 |
Accepted | 03 Jan 2018 |
Rights | Archived with thanks to IEEE Transactions on Computational Imaging |
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
Contributors | Queen's University, Belfast |
File | File Access Level Open |
File | File Access Level Open |
https://repository.derby.ac.uk/item/9396q/blind-image-watermark-detection-algorithm-based-on-discrete-shearlet-transform-using-statistical-decision-theory
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