scholarly journals A HEVC Steganalysis Algorithm Based on Relationship of Adjacent Intra Prediction Modes

2020 ◽  
Author(s):  
Henan Shi ◽  
Tanfeng Sun ◽  
Zhaohong Li

Abstract Currently, many High Efficiency Video Coding (HEVC) video steganography algorithms based on Intra Prediction Mode (IPM) have been proposed. However, the existing IPM-based video steganalysis algorithms are almost designed for H.264/AVC videos, without considering the unique coding techniques in HEVC, which is the latest video codec standard. Thus, it is of significant value to study IPM-based steganalysis for HEVC videos. In this paper, the general process of IPM-based HEVC steganography is modelled for the first time, and we find that the basic distortion existing in the change of the relationships between each embedded IPM and the adjacent IPMs. By exploiting these weaknesses, we propose a novel IPM steganalysis algorithm based on the Relationship of Adjacent IPMs (RoAIPM) feature. In detail, the RoAIPM is extracted by generating different directional Gray-Level Co-occurrence Matrixes (GLCMs) and texture characteristics of three refilled matrixes: MPM-IPM matrix, Left-IPM matrix and Up-IPM matrix. Experimental results show that, the proposed RoAIPM feature is very sensitive to the little change introduced by IPM-based steganography. Regardless of whether the feature is after dimension reduction or not, in various coding conditions, the proposed steganalysis can both present a well higher detection accuracy against the latest IPM-based HEVC steganography methods and achieve the lowest computational complexity compared with the state-of-the-art works.

2021 ◽  
Vol 13 (6) ◽  
pp. 0-0

Aiming at the problem that the data hiding algorithm of high efficiency video coding (HEVC) has great influence on the video bit rate and visual quality, an information hiding algorithm based on intra prediction mode and matrix coding is proposed. Firstly, 8 prediction modes are selected from 4×4 luminance blocks in I frame to embed the hidden information. Then, the Least Significant Bit (LSB) algorithm is used to modulate the LSB of the last prediction mode. Finally, the modulated luminance block is re-encoded to embed 4 bits secret information. Experimental results show that the algorithm improves the embedding capacity, guarantees the subjective and objective quality of the video, and the bit rate increases by 1.14% on average.


2014 ◽  
Vol 926-930 ◽  
pp. 3342-3345
Author(s):  
Chun Jiang Duanmu ◽  
Duo Dong ◽  
Xu Qiang Yang

In order to meet the trend and consumer demands for video information, the ISO/IEC group and ITU-T video encoding expert group have cooperated in making the new video encoding standard of HEVC. It defines 35 Intra prediction modes and thus has a very high encoding complexity. In order to reduce this complexity, this paper has proposed a new algorithm to effectively reduce the number of the candidate mode which needs to be checked. The edge detection and Hough transform are utilized for the prediction unit (PU) with different sizes. Statistical analysis is utilized for the detected edge line angles to decide the candidate modes that need to be checked. The C++ and OpenCV language have been utilized for the implementation of the proposed algorithm. The proposed algorithm can reduce the encoding time by 43.72 percent at most and 17.06 percent at least with just little increase of the code rate and small decrease of the PSNR.


2021 ◽  
Vol 13 (6) ◽  
pp. 1-15
Author(s):  
Yong Liu ◽  
Dawen Xu

Aiming at the problem that the data hiding algorithm of high efficiency video coding (HEVC) has great influence on the video bit rate and visual quality, an information hiding algorithm based on intra prediction mode and matrix coding is proposed. Firstly, 8 prediction modes are selected from 4×4 luminance blocks in I frame to embed the hidden information. Then, the Least Significant Bit (LSB) algorithm is used to modulate the LSB of the last prediction mode. Finally, the modulated luminance block is re-encoded to embed 4 bits secret information. Experimental results show that the algorithm improves the embedding capacity, guarantees the subjective and objective quality of the video, and the bit rate increases by 1.14% on average.


Author(s):  
Wenchan Jiang ◽  
Ming Yang ◽  
Ying Xie ◽  
Zhigang Li

High efficiency video coding (HEVC) has been deemed as the newest video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. In this research project, in compliance with H.265 standard, the authors focused on improving the performance of encode/decode by optimizing the partition of prediction block in coding unit with the help of supervised machine learning. The authors used Keras library as the main tool to implement the experiments. Key parameters were tuned for the model in the convolution neuron network. The coding tree unit mode decision time produced in the model was compared with that produced in the reference software for HEVC, and it was proven to have improved significantly. The intra-picture prediction mode decision was also investigated with modified model and yielded satisfactory results.


2019 ◽  
Vol 17 (6) ◽  
pp. 2047-2063
Author(s):  
Taha T. Alfaqheri ◽  
Abdul Hamid Sadka

AbstractTransmission of high-resolution compressed video on unreliable transmission channels with time-varying characteristics such as wireless channels can adversely affect the decoded visual quality at the decoder side. This task becomes more challenging when the video codec computational complexity is an essential factor for low delay video transmission. High-efficiency video coding (H.265|HEVC) standard is the most recent video coding standard produced by ITU-T and ISO/IEC organisations. In this paper, a robust error resilience algorithm is proposed to reduce the impact of erroneous H.265|HEVC bitstream on the perceptual video quality at the decoder side. The proposed work takes into consideration the compatibility of the algorithm implementations with and without feedback channel update. The proposed work identifies and locates the frame’s most sensitive areas to errors and encodes them in intra mode. The intra-refresh map is generated at the encoder by utilising a grey projection method. The conducted experimental work includes testing the codec performance with the proposed work in error-free and error-prone conditions. The simulation results demonstrate that the proposed algorithm works effectively at high packet loss rates. These results come at the cost of a slight increase in the encoding bit rate overhead and computational processing time compared with the default HEVC HM16 reference software.


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5242
Author(s):  
Mingyuan Cao ◽  
Lihua Tian ◽  
Chen Li

Recently, many video steganography algorithms based on the intra-prediction mode (IPM) have been adaptive steganography algorithms. These algorithms usually focus on the research about mapping rules and distortion functions while ignoring the fact that adaptive steganography may not be suitable for video steganography based on the intra-prediction mode; this is because the adaptive steganography algorithm must first calculate the loss of all cover before the first secret message is embedded. However, the modification of an IPM may change the pixel values of the current block and adjacent blocks, which will lead to the change of the loss of the following blocks. In order to avoid this problem, a new secure video steganography based on a novel embedding strategy is proposed in this paper. Video steganography is combined with video encoding. Firstly, the frame is encoded by an original encoder and all the relevant information is saved. The candidate block is found according to the relevant information and mapping rules. Then every qualified block is analyzed, and a one-bit message is embedded during intra-prediction encoding. At last, if the IPM of this block is changed, the values of the residual are modified in order to keep the optimality of the modified IPM. Experimental results indicate that our algorithm has good security performance and little impact on video quality.


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