2020
DOI: 10.1007/s11042-019-08528-7
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The large capacity embedding algorithm for H.264/AVC intra-prediction mode video steganography based on linear block code over Z4

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Cited by 9 publications
(2 citation statements)
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“…the proposed Algorithm had lower time overhead and did not cause a significant increase in bit rate. Lingyu Zhang [26] proposed H.264/AVC intra prediction video steganography algorithm based on (n, k) linear block code over ring Z4 in 2020. in additional, the property of adding abelian groups and multiplicative commutative semigroup was utilized to generate the steganography code that was applied to video steganography based on intra-prediction mode (IPM-based video steganography). Experimental results showed that the performance of the proposed scheme was superior to those of the former IPM-based schemes.…”
Section: Introductionmentioning
confidence: 99%
“…the proposed Algorithm had lower time overhead and did not cause a significant increase in bit rate. Lingyu Zhang [26] proposed H.264/AVC intra prediction video steganography algorithm based on (n, k) linear block code over ring Z4 in 2020. in additional, the property of adding abelian groups and multiplicative commutative semigroup was utilized to generate the steganography code that was applied to video steganography based on intra-prediction mode (IPM-based video steganography). Experimental results showed that the performance of the proposed scheme was superior to those of the former IPM-based schemes.…”
Section: Introductionmentioning
confidence: 99%
“…Hence, video steganography has drawn more and more interest over the last few years. Generally speaking, there are four kinds of video steganography based on different positions: the intra-prediction mode [ 10 , 11 ], motion vector [ 12 , 13 ], Discrete Cosine Transform (DCT) coefficients [ 14 , 15 ] and entropy coding coefficient [ 16 ]. Because video steganography based on DCT coefficients and entropy coefficients considerably affect the video quality, only a few scholars focus on them.…”
Section: Introductionmentioning
confidence: 99%