Motion compensation of wavelet coefficients for very low bit rate video coding

Meyer, F.G.; Averbuch, Amir; Coifman, Ronald R.

doi:10.1109/icip.1997.632202

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…In our scheme, a video is taken as the input, and perform multi resolution motion estimation [8] [9] [10] by a full search block matching method [7]. Then a neural network is trained to be used later in watermark embedding.…”

Section: The Proposed Video Watermarking Schemementioning

confidence: 99%

Video Watermarking Based on Neural Networks

El'arbi¹,

Amar

Nicolas

2006

2006 IEEE International Conference on Multimedia and Expo

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In this paper, we propose a novel digital video watermarking scheme based on multi resolution motion estimation and artificial neural network. A multi resolution motion estimation algorithm is adopted to preferentially allocate the watermark to coefficients containing motion. In addition, embedding and extraction of the watermark are based on the relationship between a wavelet coefficient and its neighbor's. A neural network is given to memorize the relationships between coefficients in a 3x3 block of the image. Experimental results show that embedding watermark where picture content is moving is less perceptible. Further, it shows that the proposed scheme is robust against common video processing attacks. INTRODUCTIONThe sudden increase in watermarking interest is most likely due to the increase in concern over copyright protection of content. With the rapid growth of the Internet and the multimedia systems in distributed environments, digital data owners can easy transfer their multimedia documents across the Internet. However, current technology does not protect their copyrights properly. This leads to wide interest of multimedia security and multimedia copyright protection and it has become a great concern to copyrights owners in recent years. In the early days, encryption and control access techniques were used to protect the ownership of media. Digital watermarking, the art of hiding information in a robust and invisible manner, has been investigated as a complementary technology [1]. There are some desirable characteristics of effective watermarking techniques, including imperceptibility, robustness, and security [2]. Imperceptibility is the degree of perceptual similarity between the original and watermarked signals. It is desirable to embed the watermark in a discreet, unobtrusive manner so that the watermark is imperceptible under casual observation. Robustness is the resilience of the watermark against manipulations such as lossy compression, linear and nonlinear filtering, scaling, and cropping (Stirmark [3], dewatermarking attack [4]).Security is the ability of the watermark to resist hostile attacks. Attacks are not limited to removal of the watermark, but include watermark estimation or forgery, collusion, and ambiguity attacks.Obviously, it is desirable to have an imperceptible, robust, and secure watermarking technique.Digital watermarking has recently been extended from still images to video. Many algorithms have already been proposed in the literature. It goes from the simple adaptation of watermarking algorithm initially designed for still images [5] to the definition of specific video watermarking scheme [6]. Open paths still remain in video watermarking. This technology is indeed in its infancy and is far from being as mature as for still images.In this paper, we propose a novel approach to neural network watermarking for uncompressed video in the wavelet domain. The watermark is embedded multiple times into the host data. Before actually embedding the watermark information, it take...

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Section: The Proposed Video Watermarking Schemementioning

confidence: 99%

Video Watermarking Based on Neural Networks

El'arbi¹,

Amar

Nicolas

2006

2006 IEEE International Conference on Multimedia and Expo

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“…Wavelet expansions are highly dependent on the alignment of the signal and the discrete grid chosen for the analysis [16]. In order to perform the motion compensation in the wavelet domain, the coefficients of the transformed signal need to be predicted [12], [13]. The main difficulty of multiscale video coding lies in the fact that the decimation and expansion operations in the wavelet transform are shift-variant.…”

Section: B Motion Estimation and Compensation In Wavelet Domainmentioning

confidence: 99%

“…However, motion compensation in the wavelet domain is highly dependent on the alignment of the signal and the discrete grid chosen for the analysis. There exist very large differences between the wavelet coefficients of the original image and the one-pixel-shifted image [12], [13]. This shift-variant property happens frequently around the image edges, so motion compensation of the wavelet coefficients can be difficult.…”

Section: Introductionmentioning

confidence: 99%

Motion estimation using low-band-shift method for wavelet-based moving-picture coding

Park

Kim

2000

IEEE Trans. on Image Process.

135

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Abstract-The discrete wavelet transform (DWT) has several advantages of multiresolution analysis and subband decomposition, which has been successfully used in image processing. However, the shift-variant property is intrinsic due to the decimation process of the wavelet transform, and it makes the wavelet-domain motion estimation and compensation inefficient. To overcome the shift-variant property, a low-band-shift method is proposed and a motion estimation and compensation method in the wavelet domain is presented. The proposed method has a superior performance to the conventional motion estimation methods in terms of the mean absolute difference (MAD) as well as the subjective quality. The proposed method can be a model method for the motion estimation in wavelet domain just like the full-search block matching in spatial domain.Index Terms-Block matching, discrete wavelet transform (DWT), low-band-shift, motion estimation and compensation, wavelet block.

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“…The forward approach consists on conducting the ME in the DWT details subbands of the low level and using it to determine the motion in the higher level subbands (coarse-to-fine). Researchers like Meyer and al (Meyer, 1997) have followed the forward approach to propose a ME method with a new pyramid structure. They have taken the aliasing effect, caused by the BMA used, into consideration and build a ME system given a good perceptual quality after MC.…”

Section: Motion Estimation and Compensationmentioning

confidence: 99%