A Generalised Model for Distortion Performance Analysis of Wavelet Based Watermarking

2013

Multimedia Systems

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With the emergence of new scalable coding standards, such as JPEG2000, multimedia is stored as scalable coded bit streams that may be adapted to cater network, device and usage preferences in multimedia usage chains providing universal multimedia access. These adaptations include quality, resolution, frame rate and region of interest scalability and achieved by discarding least significant parts of the bit stream according to the scalability criteria. Such content adaptations may also effect the content protection data, such as watermarks, hidden in the original content. Many wavelet-based robust watermarking techniques robust to such JPEG2000 compression attacks are proposed in the literature. In this paper, we have categorized and evaluated the robustness of such wavelet based image watermarking techniques against JPEG2000 compression, in terms of algorithmic choices, wavelet kernel selection, subband selection, or watermark selection using a new modular framework. As most of the algorithms uses a different set of parametric combination, this analysis is particularly useful to understand the effect of various parameters on the robustness under a common platform and helpful to design any such new algorithm. The analysis also considers the imperceptibility performance of the watermark embedding, as robustness and imperceptibility are two main watermarking properties, complementary to each other.

Section: Wavelet Kernelmentioning

confidence: 99%

On robustness against JPEG2000: a performance evaluation of wavelet-based watermarking techniques

2013

Multimedia Systems

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“…At the same time one can decide the minimum modification value for a given coefficient to be modified due to the fact that a greater modification value results in poor imperceptibility and the impact of modification on imperceptibility has been shown in an embedding distortion model in [15]. With the help of this robustness analysis model, it is possible to offer an adaptive watermark weighting parameter which can control the modification value locally along with an effective coefficient selection, so that the guaranteed watermark detection is possible for a given compression ratio with a better imperceptibility.…”

Section: Conditions For Optimisationmentioning

confidence: 99%

“…We aim to specify criteria for choosing coefficients for watermark embedding, that can ensure robustness under various quality scalability adaptations of JPEG2000 encoded bitstreams. Since the imperceptibility is reciprocally related to the robustness, we can use our previous work on the imperceptibility model [15] to find the right balance between these two properties for selecting coefficients for watermark embedding.…”

Section: Introductionmentioning

confidence: 99%

The effect of quality scalable image compression on robust watermarking

2009 16th International Conference on Digital Signal Processing

2009

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The effect of quantization based compression in quality scalable image coding on the robustness of wavelet based watermarking is presented. The non-blind direct modification type watermarking is considered for the analysis presented in this paper. First we present the analysis considering any quantization parameter and then restrict it to the integer powers of two to model the bit-plane discarding based quantization used in quality scalable coding, such as JPEG2000. This work assumes that the watermark embedding and compression uses the same wavelet filters. The derived model shows the relationship between the modified coefficients and the quantization factor, which is then used to obtain the conditions for the correct watermark extraction under compression. Based on this analysis, one can select wavelet coefficients for embedding the watermark in a manner that the correct watermark extraction is possible for a given quantization level. The results show higher robustness when this model is used for embedding the watermark. The paper also evaluates the performance of the model when the watermark embedding and the compression wavelet filters are not the same.

“…The generalisation of our model is evaluated by fitting all major wavelet-based watermarking schemes into a common framework presented in [13]. Initial concepts and the results were reported earlier in the form of conference publications [11,12] while this paper discusses the proposed scheme in detail, introduces non-linear kernels in the analysis and provides exhaustive performance evaluation. The scope of this work is strictly limited to embedding distortion analysis and excludes design and development of new robust watermarking algorithm that considers the derived model.…”

Section: Introductionmentioning

confidence: 99%

Embedding Distortion Analysis in Wavelet-domain Watermarking

ACM Trans. Multimedia Comput. Commun. Appl.

2019

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Imperceptibility and robustness are two complementary fundamental requirements of any watermarking algorithm. Low strength watermarking yields high imperceptibility, but exhibits poor robustness. High strength watermarking schemes achieve good robustness but often infuse distortions resulting in poor visual quality in host image. This paper analyses the embedding distortion for wavelet based watermarking schemes. We derive the relationship between distortion, measured in mean square error (MSE), and the watermark embedding modification and propose the linear proportionality between MSE and the sum of energy of the selected wavelet coefficients for watermark embedding modification. The initial proposition assumes the orthonormality of discrete wavelet transform. It is further extended for non-orthonormal wavelet kernels using a weighting parameter, that follows the energy conservation theorems in wavelet frames. The proposed analysis is verified by experimental results for both non-blind and blind watermarking schemes. Such a model is useful to find the optimum input parameters, including, the wavelet kernel, coefficient selection and subband choices for wavelet domain image watermarking. CCS Concepts: • Security and privacy → Digital rights management.