Difference angle quantization index modulation scheme for image watermarking

Cai, Nian; Zhu, Nannan; Weng, Shaowei; Ling, Bingo Wing‐Kuen

doi:10.1016/j.image.2015.03.010

Cited by 21 publications

(5 citation statements)

References 24 publications

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“…x k + 1 ML = x n ML 1 − x n H1 2 (15) x k M = x n ML + x n H 2 (16) x k M = x n ML − x n H 2 (17) International Journal of Students' Research in Technology & Management eISSN: 2321-2543, Vol 6, No 2, 2018, pp 41-52 https://doi.org/10.18510/ijsrtm.2018.627 Figure 2 shown below is proposed block diagram for audio watermark hiding inside the cover audio file, steps are as follow:-Step 1: input Cipher audio file and generate its samples into MATLAB environment.…”

Section: Idwtmentioning

confidence: 99%

Audio Watermarking With Angle Quantization Based on Discrete Wavelet Transform and Singular Value Decomposition

Chadar¹,

Shukla²

2018

ijsrtm

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An audio watermark is a unique electronic identifier embedded in an audio signal, typically used to identify ownership of copyright. Proposed work is a new method of audio watermark hiding inside another bigger cover standard audio cover. The method includes ‘harr’ wavelet based Discrete Wavelet Transform decomposition of frequencies hence the audio samples of watermark gets hidden only those parts of cover audio where human ears are less sensible according to Human Auditory System. Proposed method also includes the Singular Value Decomposition, which is required for making our method robust against the various communication of processing attacks like compression, filtering, fading or noise addition. Proposed work is also using the concept of angular modulation which initially modifies the audio watermark in to provide extra security and also extra robustness in communication. The design is been develop on MATLAB 2013b version and verification of design o the same.

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Section: Idwtmentioning

confidence: 99%

Audio Watermarking With Angle Quantization Based on Discrete Wavelet Transform and Singular Value Decomposition

Chadar¹,

Shukla²

2018

ijsrtm

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“…Preda and Vizireanu (2015) devised an image authentication scheme which works in DCT domain. Currently, most of the existing digital watermarking algorithms still use gray images (Cai et al, 2015) as the host images, but colour images have been applied in many occasions, so digital watermarking technology based on colour image (Roldan et al, 2016;Sadreazami et al, 2015) has more research significance. Su et al (2013) proposed a blind colour image watermarking method based on DC component.…”

Section: Related Workmentioning

confidence: 99%

Exploring robust and blind watermarking approach of colour images in DWT-DCT-SVD domain for copyright protection

Kang

Wang

et al. 2018

IJESDF

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This paper presents a new robust and invisible blind watermarking approach of colour images for copyright protection in hybrid DWT-DCT-SVD domain. In the proposed method, firstly the luminance component (Y) of the cover image is decomposed up to one level of discrete wavelet transform (DWT) coefficients and the low frequency band (LL) is transformed by discrete cosine transform (DCT). Then several selected low and intermediate frequency DCT coefficients of each block are extracted to generate a feature matrix and singular value decomposition (SVD) transform is applied to the feature matrix. Finally the watermark information is embedded by modifying the singular values of the feature matrix. Experimental results demonstrate that the proposed approach outperforms some popular existing watermarking methods in robustness against median filtering, Gaussian filtering, salt and pepper noise, average filtering, Gaussian noise, histogram equalisation, and so on, especially in case of lossy JPEG compression in addition to good imperceptibility.

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“…To solve the inconsistency of quantization step between the embedded end and the receiver end, as well as the adaptability problem of quantization step, several watermarking methods have been proposed, such as rational dither modulation [14] and adaptive QIM [15]. Furthermore, to enhance the robustness of the QIM watermarking against gain attack, the quantization watermarking [16], sample projection-based quantization [17], P-norm ratio-based quantization [18], angle quantization [19], complex wavelet domain l 1 norm quantization [20], and random projectionbased quantization methods [21] have been proposed one after another.…”

Section: Introductionmentioning

confidence: 99%

Multiplicative Watermarking Method with the Visual Saliency Model Using Contourlet Transform

Liu

Huang

2021

Security and Communication Networks

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We have proposed an image adaptive watermarking method by using contourlet transform. Firstly, we have selected high-energy image blocks as the watermark embedding space through segmenting the original image into nonoverlapping blocks and designed a watermark embedded strength factor by taking advantage of the human visual saliency model. To achieve dynamic adjustability of the multiplicative watermark embedding parameter, the relationship between watermark embedded strength factor and watermarked image quality is developed through experiments with the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM), respectively. Secondly, to detect the watermark information, the generalized Gaussian distribution (GGD) has been utilized to model the contourlet coefficients. Furthermore, positions of the blocks selected, watermark embedding factor, and watermark size have been used as side information for watermark decoding. Finally, several experiments have been conducted on eight images, and the results prove the effectiveness of the proposed watermarking approach. Concretely, our watermarking method has good imperceptibility and strong robustness when against Gaussian noise, JPEG compression, scaling, rotation, median filtering, and Gaussian filtering attack.

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Difference angle quantization index modulation scheme for image watermarking

Cited by 21 publications

References 24 publications

Audio Watermarking With Angle Quantization Based on Discrete Wavelet Transform and Singular Value Decomposition

Audio Watermarking With Angle Quantization Based on Discrete Wavelet Transform and Singular Value Decomposition

Exploring robust and blind watermarking approach of colour images in DWT-DCT-SVD domain for copyright protection

Multiplicative Watermarking Method with the Visual Saliency Model Using Contourlet Transform

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