Step-projection-based spread transform dither modulation

Li, Xinchao; Liu, Ju; Sun, Jiande; Yang, Xiaohui; Liu, Wei

doi:10.1049/iet-ifs.2010.0218

Cited by 24 publications

(23 citation statements)

References 10 publications

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“…The experiments were conducted to compare the performance of the proposed scheme and other proposed STDM improvements, termed as STDM-RW [7], STDM-AdpWM [12], STDM-RDMWm [13], and LSTDM-WM [34]. Meanwhile, three kinds of attacks (Gaussian noise with mean zero variance ranging from 0 to 15; JPEG compression, where the JPEG quality factor varies from 20 to 100; and volumetric scaling attacks that can reduce the image intensities as scaling factor varies from 0.1 to 1.5) were used to verify the performance of the proposed models.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…The experimental results are demonstrated in Figure 7. From the robustness results, the proposed scheme outperforms STDM-RW [7], STDM-AdpWM [12], STDM-RDMWm [13], and LSTDM-WM [34] schemes. Our proposed scheme has average BER values 3% lower than the STDM-RW and STDM-RDMWm schemes.…”

Section: Experiments Of Robustness With Vsi = 0982mentioning

confidence: 94%

“…The maximum imperceptible changes s in the direction of u can be given as s u . Since the maximum quantization error of the quantizer is ∆/2, the quantization step ∆ in the STDM quantizer is given by ∆ = 2s u [13].…”

Section: Stdm Watermarking Using Visual Saliency-based Jnd Modelmentioning

confidence: 99%

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A Novel STDM Watermarking Using Visual Saliency-Based JND Model

et al. 2017

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Abstract:The just noticeable distortion (JND) model plays an important role in measuring the visual visibility for spread transform dither modulation (STDM) watermarking. However, the existing JND model characterizes the suprathreshold distortions with an equal saliency level. Visual saliency (VS) has been widely studied by psychologists and computer scientists during the last decade, where the distortions are more likely to be noticeable to any viewer. With this consideration, we proposed a novel STDM watermarking method for a monochrome image by exploiting a visual saliency-based JND model. In our proposed JND model, a simple VS model is employed as a feature to reflect the importance of a local region and compute the final JND map. Extensive experiments performed on the classic image databases demonstrate that the proposed watermarking scheme works better in terms of the robustness than other related methods.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Experiments Of Robustness With Vsi = 0982mentioning

confidence: 94%

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A Novel STDM Watermarking Using Visual Saliency-Based JND Model

et al. 2017

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“…Thus the maximum imperceptible change in the direction of u could be given as s T u. Since the maximum quantization error of the quantizer is ∆/2, the quantization step ∆ in the STDM quantizer is given by ∆ = 2s T u [10]. So assume x max = x+∆, where x max denotes the worst distorted signal which is imperceptible, according to (4), the difference between each transformed signal y and y max could be given as (9).…”

Section: Adaptive Logarithmic Stdm With Perceptual Modelmentioning

confidence: 99%

Logarithmic Spread-Transform Dither Modulation watermarking Based on Perceptual Model

Wan

Liu

Sun

et al. 2013

2013 IEEE International Conference on Image Processing

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Logarithmic Quantization Index Modulation (LQIM) is an important extension of the original quantization-based watermarking method. However, it is well known that it is sensitive to valumetric scaling attack and easy to result in sign error after quantization and attacks. For that, in this paper, we propose a new method, namely Logarithmic Spread-Transform Dither Modulation Based on Perceptual Model (LSTDM-WM). In this regard the host signal is first projected onto a random vector and transformed using a novel Logarithmic Quantization function. Then the transformed signal is quantized regarding the watermark data and the watermarked signal is obtained by applying inverse transform to the quantized signal. The perceptual model is further exploited to adjust the quantization step adaptively for watermark embedding. Experimental results indicate that our proposed scheme overcomes two challenges cited above and has superior performance in comparison with conventional LQIM and former proposed schemes of STDM.

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“…And then the watermark is embedded into above selected coefficients. We employ the algorithm of quantized projection based on the zigzag scanning [5]. So in that way we will mini mize the damage of the approximate horizontal movement of DlBR processing to the watermark information.…”

Section: Proposed Schemementioning

confidence: 99%

Contourlet transform based digital watermarking resisting 2D-3D conversion

Yang

Sun

Wan

et al. 2013

2013 3DTV Vision Beyond Depth (3dtv-Con)

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Nowadays with the success of 2D-3D applications, the copyright protection for such cases is becoming increasing important. In this paper, a contourlet transform based watermarking scheme is proposed, which is robust against DlBR-based 2D-3D conver sion. In the proposed scheme, the contourlet transform is per formed on the center image. Considering that the DlBR trans form can be regarded as the horizontal direction movement, coefficients of the low-frequency after contourlet transform are quantized to embed the watermark. Experimental results show that the watermark can be extracted from the virtual left and right image correctly and stably. The proposed scheme achieves better robustness and invisibility, which demonstrates that it is promising in 2D-3D conversion applications. Index Terms -Digital Watermarking; Copyright Protec tion; DlBR; 2D-3D Conversion; Contourlet Transform 1. INTRODUCTION Recently, different kinds of 2D-3D conversion applications are arising with the emerging of low cost 3D display devices. The digital watermark for such 3D media protection must play an important role for developing and promoting the 3D entertain ment industry. According to [1], the 3D watermarking systems can be classified on the basis of their embedding space and detecting space as: 3D/3D, 3D/2D and 2D/2D. The 3D/3D watermarking system embeds the watermark into a 3D (geometry or texture) model and detects the watermark also from the 3D space, while the 3D/2D watermarking system extracts the watermark in a 2D representation (acquired by projection) of a 3D data. The 2D/2D watermarking deals with the content protection of image-based 3D data representation in which all the embedding and detection operations are performed on 2D images directly. In 2D-3D conversion, a central image and the correspond ing depth image are usually needed. The related two virtual im ages corresponding to the views in human eyes are generated by the central image and associated per-pixel depth information with the DIBR technique [2]. So these two virtual images are similar to the central image perceptually. These two virtual images can be distributed as 2D images again and it causes a new copyright protection challenges. As is known to all, the copy right protection should be robust to DIBR process first and so the traditional digital watermark algorithms for 2D images can't

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Step-projection-based spread transform dither modulation

Cited by 24 publications

References 10 publications

A Novel STDM Watermarking Using Visual Saliency-Based JND Model

A Novel STDM Watermarking Using Visual Saliency-Based JND Model

Logarithmic Spread-Transform Dither Modulation watermarking Based on Perceptual Model

Contourlet transform based digital watermarking resisting 2D-3D conversion

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