Optimal and secure audio watermarking scheme based on self-adaptive particle swarm optimization and quaternion wavelet transform

Lei, Baiying; Zhou, Feng; Tan, Eng Leong; Ni, Dong; Lei, Haijun; Chen, Siping; Wang, Tianfu

doi:10.1016/j.sigpro.2014.11.007

Cited by 37 publications

(24 citation statements)

References 37 publications

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“…Wang et al proposed a DCT‐based method to put the watermark in the middle frequency coefficients and make the watermark insertion process nearly lossless . Lei et al embedded the watermark in the singular values of low‐frequency coefficients based on QWT to improve watermark robustness …”

Section: Methodsmentioning

confidence: 99%

“…Essentially, the QWT is an analytic signal with a shift‐invariant magnitude and three phases that can explicitly describe image content. Therefore, the QWT‐based watermarking method not only addresses the common drawbacks in standard wavelet transforms by providing the shift‐invariant feature but also exhibits superiority over the QFT because of its multiscale property . For instance, the QWT‐based watermarking method has demonstrated high robustness against many signal processing manipulations .…”

Section: Introductionmentioning

confidence: 99%

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Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition

Che

Luo

et al. 2019

Math Methods in App Sciences

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Digital watermarking is important for protecting the intellectual property of remote sensing images. Unlike watermarking in ordinary colour images, in colour remote sensing images, watermarking has an important requirement: robustness. In this paper, a robust nonblind watermarking scheme for colour remote sensing images, which considers both frequency and statistical pattern features, is constructed based on the quaternion wavelet transform (QWT) and tensor decomposition. Using the QWT, not only the abundant phase information can be used to preserve detailed host image features to improve the imperceptibility of the watermark, but also the frequency coefficients of the host image can provide a stable position to embed the watermark. To further strengthen the robustness, the global statistical feature structure acquired through the tensor Tucker decomposition is employed to distribute the watermark's energy among different colour bands. Because both the QWT frequency coefficients and the tensor decomposition global statistical feature structure are highly stable against external distortion, their integration yields the proposed scheme, which is robust to many image manipulations. A simulation experiment shows that our method can balance the trade‐off between imperceptibility and robustness and that it is more robust than the traditional QWT and discrete wavelet transform (DWT) methods under many different types of image manipulations.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition

Che

Luo

et al. 2019

Math Methods in App Sciences

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“…Data hiding algorithms with high capacity and low robustness are called steganography techniques, while the general term of watermarking usually refers to a low-capacity robust data hiding scheme. The capacity of a data hiding scheme defined as [53]:…”

Section: Capacitymentioning

confidence: 99%

“…In the last two decades, artificial intelligence (AI) techniques such as evolutionary algorithms (EAs), support vector machine, fuzzy logic and neural networks have played an important role in data hiding [25,71,72,83,95,94,99,105,116,121] for improving the performance. Under the category of evolutionary algorithms, genetic algorithm (GA) [7,23,25,47,71,72,81], particle swarm optimization (PSO) [53,85,94,99,108], differential evolution (DE) [4,6,2,8,52], Firefly algorithm [76], and artificial bee colony (ABC) [5] have made numerous valuable contributions to the field of data hiding. An image watermarking technique which uses a GA to find the optimal scaling factors for watermark insertion is designed by Lai [47].…”

Section: Application Of Artificial Intelligence In Data Hidingmentioning

confidence: 99%

“…Fındık et al [29], have applied the PSO for color image watermarking. A new audio watermarking scheme based on self-adaptive particle swarm optimization (SAPSO) and quaternion wavelet transform (QWT) is proposed by Lei et al [53]. By obtaining optimal watermark strength using a uniquely designed objective function, SAPSO addresses the conflicting problem of robustness, imperceptibility, and capacity of audio watermarking scheme using self-adjusted parameters.…”

Section: Application Of Artificial Intelligence In Data Hidingmentioning

confidence: 99%

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Data Hiding Schemes: A Survey

Ali¹,

Ahn²,

Pant³

2016

Gate to Computer Science and Research

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Data hiding is the process of hiding an amount of data, called secret message or watermark, into a cover media that may be audio, video, or image signal, in an imperceptible way for different purposes. Due to the advances in generation, storage, and communication technology of digital media, the necessity and importance of data hiding has drawn the attention of many researchers all over the world resulting in a lot of variants of data hiding scheme. This chapter provides a detailed review of the basic concepts of data hiding and a survey of its major variants developed so far. The chapter classifies the data hiding schemes based on several aspects of data hiding comprising artificial intelligence. Furthermore, the chapter also provides the recommendations to the interested users for further research. This review may be a useful insight and a good source for the users who are interested in the application of artificial intelligence in data hiding.

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Gram–Schmidt Orthogonalization-Based Audio Multiple Watermarking Scheme

Yuan

2020

Circuits Syst Signal Process

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Optimal and secure audio watermarking scheme based on self-adaptive particle swarm optimization and quaternion wavelet transform

Cited by 37 publications

References 37 publications

Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition

Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition

Data Hiding Schemes: A Survey

Gram–Schmidt Orthogonalization-Based Audio Multiple Watermarking Scheme

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