Motion and disparity vectors early determination for texture video in 3D-HEVC

Pan, Zhaoqing; Yi, Xiaokai; Chen, Liming

doi:10.1007/s11042-018-6830-7

Cited by 29 publications

(28 citation statements)

References 22 publications

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“…However, the adaptive steganography usually can't extract the secret messages exactly and correctly when the stego image suffer from image processing attacks, such as compression, scaling, and so on. Similar situations exist in other multimedia fields such as video [2], [3]. In practice, most digital images are obtained and transmitted through electronic devices such as mobile phones and tablets, while others are computer generated images [4].…”

Section: Introductionmentioning

confidence: 64%

Zernike Moment-Based Spatial Image Steganography Resisting Scaling Attack and Statistic Detection

Zhang¹,

Luo²,

Guo

et al. 2019

IEEE Access

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The mainstream adaptive steganography algorithm is difficult to resist scaling attack, and the anti-detection performance of the algorithm based on quantization index modulation is not high enough. To solve the above problems, this paper proposes a spatial image adaptive steganography algorithm based on Zernike moment to resist scaling attack and statistic detection. First, the Zernike moment of the normalized cover image is extracted and the new cover is obtained by the dither modulation algorithm. Second, the minimized distortion embedding is realized by Spatial UNIversal WAvelet Relative Distortion (S-UNIWARD) and syndrome-trellis codes coded. And finally, the stego image is generated by changing the original Zernike moment according to the modified amplitude of the new cover. The experimental results show that the proposed algorithm is robust to the three common scaling attacks, and the message extraction error rate is significantly lower than the S-UNIWARD steganography after the scaling attacks; moreover, compared with the steganography algorithm based on quantization index modulation, the proposed algorithm has higher detection resistance.

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Section: Introductionmentioning

confidence: 64%

Zernike Moment-Based Spatial Image Steganography Resisting Scaling Attack and Statistic Detection

Zhang¹,

Luo²,

Guo

et al. 2019

IEEE Access

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“…A fast mode decision is proposed in [29] to reduce candidate modes of 3D-HEVC, where the inter-view and grayscale similarity correlation are jointly used. A motion and disparity vectors early determination algorithm is proposed in [30], which exploits the spatial and temporal motion vector of neighboring treeblocks to reduce 3D-HEVC computational complexity. Up to 33.0% complexity reduction is reported with insignificant RD performance loss for texture video coding.…”

Section: Related Workmentioning

confidence: 99%

“…Tables 14 and 15 compare the proposed overall algorithm with two state-of-the-art fast methods, fast encoder decision for texture coding (FEDTC) [25], and OLCRS [28] based on the "CTC" condition. e QP values used for the texture and depth are chosen as follows: (25,34), (30,39), (35,42), and (40,45). All algorithms are executed on a computer for comparison.…”

Section: Performance Comparison With the State-of-the-artmentioning

confidence: 99%

Low-Complexity Texture Video Coding Based on Motion Homogeneity for 3D-HEVC

Zhang

Shuaichao

2019

Scientific Programming

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Three-dimensional extension of the high efficiency video coding (3D-HEVC) is an emerging international video compression standard for multiview video system applications. Similar to HEVC, a computationally expensive mode decision is performed using all depth levels and prediction modes to select the least rate-distortion (RD) cost for each coding unit (CU). In addition, new tools and intercomponent prediction techniques have been introduced to 3D-HEVC for improving the compression efficiency of the multiview texture videos. These techniques, despite achieving the highest texture video coding efficiency, involve extremely high-complex procedures, thus limiting 3D-HEVC encoders in practical applications. In this paper, a fast texture video coding method based on motion homogeneity is proposed to reduce 3D-HEVC computational complexity. Because the multiview texture videos instantly represent the same scene at the same time (considering that the optimal CU depth level and prediction modes are highly multiview content dependent), it is not efficient to use all depth levels and prediction modes in 3D-HEVC. The motion homogeneity model of a CU is first studied according to the motion vectors and prediction modes from the corresponding CUs. Based on this model, we present three efficient texture video coding approaches, such as the fast depth level range determination, early SKIP/Merge mode decision, and adaptive motion search range adjustment. Experimental results demonstrate that the proposed overall method can save 56.6% encoding time with only trivial coding efficiency degradation.

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“…It has been widely used in video surveillance, network TV, HD video and other fields [16], [17]. Considering the characteristics of the H.264 standard, each 16 × 16 residual macroblock in the P frame (forward prediction frame) is used as an embedding position [18], [19]. To avoid the influence of video compression on the embedded information, the information is embedded in the quantized DCT coefficients.…”

Section: Video Steganography Algorithm Under Hybird Model a Algomentioning

confidence: 99%

Hybrid Adaptive Video Steganography Scheme Under Game Model

Niu

Yang

et al. 2019

IEEE Access

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The steganographic model based on game theory is improved. A hybrid steganography model that satisfies the Kerckhoffs principle by combining the strategy adaptation of the game theory model and the content adaptation in the cover model is proposed. This model is used to design a high-security steganography algorithm for an H.264 video. The distortion function in UNIWARD algorithm is improved according to the H.264 video coding characteristics. The improved distortion function is used to generate the bias function under the game theory model, and the embedding probability of each position in the cover is calculated. The new distortion function under the hybrid model is generated by combining the embedding probability of the cover position and the distortion cost function under the improved UNIWARD algorithm and using it to embed information in the H.264 residual DCT coefficient block. The experiment proves that the algorithm has higher security than the UNIWARD algorithm. With the same analysis algorithm, the detection error rate is significantly improved compared to the UNIWARD algorithm. The algorithm has a large embedding capacity and good invisibility. When fully embedded, the capacity reaches 1.9% or more, the visual effect does not change significantly, and the PSNR value decreases within 2 dB. After the secret message is embedded in the information, the video bit rate is increased by 9%. INDEX TERMS Video steganography, game theory model, hybrid adaptive, H.264 encoding.

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Motion and disparity vectors early determination for texture video in 3D-HEVC

Cited by 29 publications

References 22 publications

Zernike Moment-Based Spatial Image Steganography Resisting Scaling Attack and Statistic Detection

Zernike Moment-Based Spatial Image Steganography Resisting Scaling Attack and Statistic Detection

Low-Complexity Texture Video Coding Based on Motion Homogeneity for 3D-HEVC

Hybrid Adaptive Video Steganography Scheme Under Game Model

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