Digital watermarking in joint time-frequency domain

Mobasseri, Bijan G.

doi:10.1109/icip.2002.1039012

Cited by 29 publications

(25 citation statements)

References 4 publications

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“…The decoder then reconstructs v and uses it as a pointer in (β, f ) plane to recover the V pairs of (β 0 , f 0 ). Using the correct key will cause a peak in (5) signaling that the image carries a watermark. If the key is not known, the decoder must do an exhaustive search over all anticipated combinations of (β 0 , f 0 ).…”

Section: Watermark Recoverymentioning

confidence: 98%

“…Use of the chirp is part of a broader approach to watermarking using time-frequency representations [5][6][7][8][9]. For example, [5] and [8] utilize bilinear time-frequency transformations and the watermark is embedded in the joint time-frequency domain. Watermarking in time-frequency domain has also been used in fragile watermarking applications [9].…”

Section: Introductionmentioning

confidence: 99%

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Image-adaptive watermarking using 2D chirps

Zhang

Mobasseri

Dogahe

et al. 2009

SIViP

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Linear chirps, a special case of polynomial phase exponentials, have recently been proposed for digital watermarking. In this work, we propose a known-host-state methodology for designing image watermarks that are robust to compression. We use a two-dimensional frequencymodulated chirp as a spreading function in a block-based spatial watermarking scheme. In each block, the chirp is used to embed binary phase information. Chirp parameters allow for spectral shaping of the watermark to match host content. Since host state is known to the embedder, it is possible to tune the chirp for optimum performance, particularly against compression. In contrast to existing chirp watermarking where only a single watermark is generally embedded, the proposed block chirp watermarking allows for a much higher payload. Detection is done using chirp transform subject to key exchange for security. We show that the proposed method significantly outperforms non-adaptive watermarking across all compression factors under variety of attacks.

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Section: Watermark Recoverymentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Image-adaptive watermarking using 2D chirps

Zhang

Mobasseri

Dogahe

et al. 2009

SIViP

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show abstract

“…We should note that for this semi-private watermarking technique, the knowledge of the Radon-Wigner distribution of the original image is necessary in the detection process. The approach in [9] uses the Wigner distribution. Specifically, the Wigner distribution of the image is added to the time-frequency watermark [9].…”

Section: Introductionmentioning

confidence: 99%

A new time-frequency based private fragile watermarking scheme for image authentication

Barkat

Sattar

2003

Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings.

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In this paper, a new private fragile image watermarking scheme is proposed for image authentication based on time-frequency analysis. Specifically, the watennark is chosen as an arbitrary nonstationary signal with a particular signature in the time-frequency plane. The proposed technique retains a high quality watermarked image since only a few pixels of the original image are used in the watermarking process. Experimental results show that the pmposed fragile watermark is very sensitive to many attacks such as cropping, scaling, translation and JPEG compression, making it very effective in image authentication.

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“…While in the spectral domain, the watermark is embedded in the transform domain using methods such as DCT and DWT, in the mid-frequency range to ensure transparency and robustness of the watermark, simultaneously [2,3]. In order to take full advantage of both the spatial and the transform domains, researchers started looking at the joint spatial-spectral representation of the image, which gives a more comprehensive representation of the image [4,5,6,7]. The joint spatialspectral domain provides flexibility in how much data can be hidden and where it should be hidden inside an image.…”

Section: Introductionmentioning

confidence: 99%

“…In [5], the Wigner distribution is used for watermarking. The watermark is embedded in a subset of the transformed cells selected such that the watermark will survive the JPEG compression.…”

Section: Introductionmentioning

confidence: 99%

Robust Watermarking in the Wigner Domain

Al-khassaweneh

Aviyente

2006

2006 IEEE International Conference on Multimedia and Expo

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In this paper, a new watermarking scheme in the joint timefrequency domain is introduced. Wigner distribution is used to transform an image into the spatial-spectral domain. The proposed method selects the time-frequency cells to be watermarked based on the particular image's energy distribution in the joint domain. This approach ensures the imperceptibility of the embedded watermark. It is shown that embedding in the time-frequency domain is equivalent to a nonlinear embedding function in the spatial domain. A corresponding watermark detection algorithm is also introduced. The performance of the proposed watermarking algorithm under possible attacks, such as noise, re-sampling, rotation, filtering, and JPEG compression is illustrated.

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Digital watermarking in joint time-frequency domain

Cited by 29 publications

References 4 publications

Image-adaptive watermarking using 2D chirps

Image-adaptive watermarking using 2D chirps

A new time-frequency based private fragile watermarking scheme for image authentication

Robust Watermarking in the Wigner Domain

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