High Efficiency Video Coding Video Research Articles

Data embedding in high efficiency video coding (HEVC) videos by modifying the partitioning of coding units

A data embedding solution in HEVC videos is proposed by modifying the partitioning of coding units (CUs). The partitions of a CU are first represented as a sequence of binary flags. The flags pertaining to 16 × 16 sub CUs are used as a cover for data embedding, where 6 or 4 message bits are embedded per CU. The data embedding algorithm guarantees that a maximum of one partition is modified per message segment, therefore, in a given CU, either 0, 1 or 2 partitions are modified. The proposed solution is assessed in terms of message payload, number of modified partitions, loss in video quality as indicated by the PSNR results, mean objective scores and excessive bitrate. The proposed solution can embed messages with up to an average payload of 32.6 kbit/s with a corresponding average distortion of <0.5 dB. Comparisons with existing solutions reveal that the proposed solution maintains similar message payloads with less modifications of CU partitioning and at the same time resulting in less distortions for the cover video.

High Capacity HEVC Video Hiding Algorithm Based on EMD Coded PU Partition Modes

Data hiding in videos has been a big concern as their rich redundancy can be used for embedding a lot of secret information. Further, as high efficiency video coding (HEVC) introduces many innovative technologies compared with the previous standard, H.264, it has gradually become the mainstream. Therefore, it is valuable to develop new information hiding algorithms by using novel features of HEVC. A HEVC video data hiding algorithm based on prediction unit (PU) partition modes from inter prediction process is proposed in this paper. Firstly, code units (CUs) in two sizes of 8 × 8 and 16 × 16 are selected for embedding, then the PU partition modes in these CUs are coded by a spatial coding method. After that, two specific hiding algorithms by modifying coded PU partition modes in CUs of 8 × 8 and 16 × 16 are proposed, respectively. Experimental results show that the proposed algorithm has achieved excellent performance with high visual quality, and high embedding capacity and low bitrate increase in both high- and low-resolution videos compressed with different quantization parameters (QPs). Compared with the state-of-the-art work, the proposed algorithm achieves a much higher capacity while keeping quite high visual quality with little increase of bitrate.

Fake Bitrate Detection of HEVC Videos Based on Prediction Process

In order to defraud click-through rate, some merchants recompress the low-bitrate video to a high-bitrate one without improving the video quality. This behavior deceives viewers and wastes network resources. Therefore, a stable algorithm that detects fake bitrate videos is urgently needed. High-Efficiency Video Coding (HEVC) is a worldwide popular video coding standard. Hence, in this paper, a robust algorithm is proposed to detect HEVC fake bitrate videos. Firstly, five effective feature sets are extracted from the prediction process of HEVC, including Coding Unit of I-picture/P-picture partitioning modes, Prediction Unit of I-picture/P-picture partitioning modes, Intra Prediction Modes of I-picture. Secondly, feature concatenation is adopted to enhance the expressiveness and improve the effectiveness of the features. Finally, five single feature sets and three concatenate feature sets are separately sent to the support vector machine for modeling and testing. The performance of the proposed algorithm is compared with state-of-the-art algorithms on HEVC videos of various resolutions and fake bitrates. The results show that the proposed algorithm can not only can better detect HEVC fake bitrate videos, but also has strong robustness against frame deletion, copy-paste, and shifted Group of Picture structure attacks.

HEVC double compression detection under different bitrates based on TU partition type

During the process of authenticating the integrity of digital videos, double compression is an important evidence. High-efficiency video coding (HEVC) is the latest coding standard proposed in 2013 and has shown superior performance over its predecessors. It brings in several novel syntactic units, such as coding tree unit (CTU), prediction unit (PU), and transform unit (TU). Few methods have been reported to detect HEVC double compression by utilizing such new characteristics. In this paper, a novel scheme based on TU is proposed to detect double compression of HEVC videos. The histogram of each TU partition type in the first I/P frame of all GOPs is calculated. The feature set is fed into SVM to classify single and double compressed videos. Experimental results have demonstrated the effectiveness of TU-based feature (accuracy in [0.84, 0.97]) that bears very low dimension (10-D). And it is also shown that TU-based feature set can be combined with other feature sets to boost their performance.

Detection of HEVC Double Compression With the Same Coding Parameters Based on Analysis of Intra Coding Quality Degradation Process

The emergence of the high-efficiency video coding (HEVC) standard enables people to enjoy high definition (HD) video content; meanwhile, HD videos, tamper detection has become a crucial issue and gradually aroused people’s attention. The detection of double HEVC compressed videos with the same coding parameters is challenging since the recompression traces are inconspicuous. To deal with this issue, a novel method based on the intra prediction mode is proposed in this paper. First, the quality degradation mechanism is analyzed to facilitate the selection of classification features and the source of error in intra coding is fully considered to establish the equivalent error model. Second, the feature model of double HEVC compression detection, which is mainly based on the statistical feature of intra prediction mode, is proposed. Finally, the experiment is carried out in 720p and 1080p HEVC videos instead of low-resolution (CIF or QCIF) videos. Experimental results have demonstrated better efficiency of the proposed method in comparison to the state-of-the-art methods. Besides, the proposed method is more robust to various encoding configurations.

Effectiveness of crypto-transcoding for H.264/AVC and HEVC video bit-streams

To avoid delays arising from a need to decrypt a video prior to transcoding and then re-encrypt it afterwards, this paper assesses a selective encryption (SE) content protection scheme. The scheme is suited to both recent standardized codecs, namely H.264/Advanced Video Coding (AVC) and High Efficiency Video Coding (HEVC). Specifically, the paper outlines a joint crypto-transcoding scheme for secure transrating of a video bitstream. That is to say it generates new video bitrates, possibly as part of an HTTP Adaptive Streaming (HAS) content delivery network. The scheme will reduce the bitrate to one or more lower desired bit-rate without consuming time in the encryption/decryption process, which would be the case when full encryption is used. In addition, the decryption key no longer needs to be exposed at intermediate middleboxes, including when transrating is performed in a cloud datacenter. The effectiveness of the scheme is variously evaluated: by examination of the SE generated visual distortion; by the extent of computational and bitrate overheads; and by choice of cipher when encrypting the selected elements within the bitstream. Results indicate that there remains: a content; quantization level (after transrating of an encrypted video); and codec-type dependency to any distortion introduced. A further recommendation is that the Advanced Encryption Standard (AES) is preferred for SE to lightweight XOR encryption, despite it being taken up elsewhere as a real-time encryption method.

Detection of double compression in HEVC videos based on TU size and quantised DCT coefficients

With the advent of sophisticated and low-cost video editing software, digital videos are highly vulnerable to be tampered. The authenticity and integrity identification of digital videos is an urgent issue. In this study, an effective method to detect double High Efficiency Video Coding (HEVC) video compression with different quantisation parameter (QP) is proposed, which often occurs in the video tampering process. First, the effects of QP on the distributions of Discrete Cosine Transform (DCT) coefficients and Transform Unit (TU) size are analysed. Then a feature set including 17 features is derived from quantised DCT coefficients and TU size. It can characterize the statistical differences between single and double compressed videos. Finally, the Library for Support Vector Machine classifier is exploited to identify whether a given HEVC video has been double compressed or not. Experimental results demonstrate that the authors' detection method has a good comprehensive performance.

A HEVC Video Steganalysis Algorithm Based on PU Partition Modes

Steganalysis is a technique used for detecting the existence of secret information embedded into cover media such as images and videos. Currently, with the higher speed of the Internet, videos have become a kind of main methods for transferring information. The latest video coding standard High Efficiency Video Coding (HEVC) shows better coding performance compared with the H.264/AVC standard published in the previous time. Therefore, since the HEVC was published, HEVC videos have been widely used as carriers of hidden information. In this paper, a steganalysis algorithm is proposed to detect the latest HEVC video steganography method which is based on the modification of Prediction Units (PU) partition modes. To detect the embedded data, All the PU partition modes are extracted from P pictures, and the probability of each PU partition mode in cover videos and stego videos is adopted as the classification feature. Furthermore, feature optimization is applied, that the 25-dimensional steganalysis feature has been reduced to the 3-dimensional feature. Then the Support Vector Machine (SVM) is used to identify stego videos. It is demonstrated in experimental results that the proposed steganalysis algorithm can effectively detect the stego videos, and much higher classification accuracy has been achieved compared with state-of-the-art work.

High capacity and multilevel information hiding algorithm based on pu partition modes for HEVC videos

In order to realize copyright protection and piracy tracking for ever-increasing videos, video information hiding has gained more and more attention. For the latest video coding standard — High Efficiency Video Coding (HEVC), most of the information hiding algorithms are based on the same characteristics as those in MPEG4 and H.264, such as DCT coefficients, intra prediction modules and motion vectors. However, few algorithms are reported to hide information based on the innovation modules introduced by HEVC. This paper has proposed a high capacity and multilevel information hiding algorithm based on PU partition modes in P-frames, which is considered to be one of the most important innovative features of HEVC. The proposed algorithm consists of two stages: first round calculation and modification process. The first round calculation is to record the PU partition modes selected by HEVC. The modification process is to force each of PU mode into one of the encoded groups according to the embedding binary bits, and then use the modified PU partition modes for the left HEVC encoding process. The experimental results show that the proposed algorithm can achieve high capacity and visual quality, and low bit rate increase, which significantly outperforms state-of-the-art works in embedding capacity.

Enhanced adaptive cross-layer scheme for low latency HEVC streaming over Vehicular Ad-hoc Networks (VANETs)

Vehicular communication has become a reality guided by various applications. Among those, high video quality delivery with low latency constraints required by real-time applications constitutes a very challenging task. By dint of its never-before-achieved compression level, the new High-Efficiency Video Coding (HEVC) is very promising for real-time video streaming through Vehicular Ad-hoc Networks (VANET). However, these networks have variable channel quality and limited bandwidth. Therefore, ensuring satisfactory video quality on such networks is a major challenge. In this work, a low complexity cross-layer mechanism is proposed to improve end-to-end performances of HEVC video streaming in VANET under low delay constraints. The idea is to assign to each packet of the transmitted video the most appropriate Access Category (AC) queue on the Medium Access Control (MAC) layer, considering the temporal prediction structure of the video encoding process, the importance of the frame and the state of the network traffic load. Simulation results demonstrate that for different targeted low-delay video communication scenarios, the proposed mechanism offers significant improvements regarding video quality at the reception and end-to-end delay compared to the Enhanced Distributed Channel Access (EDCA) adopted in the 802.11p. Both Quality of Service (QoS) and Quality of Experience (QoE) evaluations have been also carried out to validate the proposed approach.

HEVC transforms with reduced elements bit depth

High-efficiency video coding (HEVC) is based on integer discrete cosine transforms (DCTs) of size 4 × 4, 8 × 8, 16 × 16 and 32 × 32 whose elements are coded on 8 bits. However, the algorithm requires that the output length at each processing stage should never exceed 16 bits. The conventional solution is the truncation of the least significant bits which leads to erroneous results and a waste of resources. In this Letter, different DCT kernels with reduced elements length are proposed. They are evaluated for compression efficiency and hardware implementation competence. An implementation on the Xilinx FPGA virtex-6 circuit has given a maximal operating frequency increase of 4.81 and 93.41% for the DCT-II 4 × 4 and the discrete sine transform, while reducing the energy consumption by 10.64 and 30.77% at 100 MHz, respectively. Using the HM 16.3 HEVC model and video sequences of different resolutions, the results show a quality degradation of 0.01 dB for a bit rate increase of 0.19% compared to the reference cores.

A 120 fps High Frame Rate Real-time HEVC Video Encoder with Parallel Configuration Scalable to 4K

This paper describes a new 120 fps (frames per second) real-time HEVC (High Efficiency Video Coding) encoder for HFR (high frame rate) video encoding and transmission. HFR provides more immersive viewing experience features by solving the problems created by fast moving scenes. Temporally scalable encoding with backward compatibility for legacy non-HFR systems is suitable for the rapid spread of HFR content delivery, avoiding the need to distribute multiple bitstreams of the same video with different frame rates. Such temporal scalability requires flexible encoder control functionalities to support newly-customized reference picture structures and dual-stream bitrate control. In this paper, modification in the customizable software architecture of encoder LSIs makes it possible to achieve 120 fps temporally scalable HEVC encoding for existing 60 fps-based systems. The encoder also achieves ${4\mathrm{K}/ 120\;\mathrm{fps}}$ video encoding in real time through the synchronized operation of multiple ${2\mathrm{K}/ 120\;\mathrm{fps}}$ encoders working in parallel. Our evaluations show that the bitrate increase rate from 60 fps to 120 fps under the same objective image quality condition are within the range of less than 57.2 percent in all video sequences and its average value is 53.8 percent. Both values are lower than that of the HM (HEVC reference software). The proposed encoder systems will open the door to the next generation high frame rate UHDTV (ultra high definition television) services.

Enhancing Quality for HEVC Compressed Videos

The latest High Efficiency Video Coding (HEVC) standard has been increasingly applied to generate video streams over the Internet. However, HEVC compressed videos may incur severe quality degradation, particularly at low bit-rates. Thus, it is necessary to enhance the visual quality of HEVC videos at the decoder side. To this end, this paper proposes a Quality Enhancement Convolutional Neural Network (QE-CNN) method that does not require any modification of the encoder to achieve quality enhancement for HEVC. In particular, our QE-CNN method learns QE-CNN-I and QE-CNN-P models to reduce the distortion of HEVC I and P frames, respectively. The proposed method differs from the existing CNN-based quality enhancement approaches, which only handle intra-coding distortion and are thus not suitable for P frames. Our experimental results validate that our QE-CNN method is effective in enhancing quality for both I and P frames of HEVC videos. To apply our QE-CNN method in time-constrained scenarios, we further propose a Time-constrained Quality Enhancement Optimization (TQEO) scheme. Our TQEO scheme controls the computational time of QE-CNN to meet a target, meanwhile maximizing the quality enhancement. Next, the experimental results demonstrate the effectiveness of our TQEO scheme from the aspects of time control accuracy and quality enhancement under different time constraints. Finally, we design a prototype to implement our TQEO scheme in a real-time scenario.

Anti-HEVC Recompression Video Watermarking Algorithm Based on the All Phase Biorthogonal Transform and SVD

ABSTRACTWith the rapid development of Internet of Things and multimedia technologies, people are paying more attention to the security of images and videos. To further improve the security of video content, a video watermarking algorithm based on the high efficiency video coding (HEVC) compression domain is proposed in this paper. The scheme embeds watermark information in the quantized coefficients, which can solve the cumulative error caused by watermark embedding. Moreover, the all phase biorthogonal transform (APBT), an improved transform, is used to compress the watermark data at the digital watermark preprocessing stage, optimize the watermark embedding scheme, and improve the embedding capacity of video watermarking. Due to the characteristics of HEVC video coding, most HEVC video watermarking schemes based on compression domain cannot resist recompression attack. To solve this problem, on the basis of APBT and singular value decomposition, an anti-HEVC recompression video watermarking algorithm is proposed and can effectively resist the HEVC recompression. Experimental results show that even when the quantization parameter is larger than 40, the extracted watermark still has good image quality. In addition, the algorithm also has a good performance in noise resistance.

Frame-Based and Subpicture-Based Parallelization Approaches of the HEVC Video Encoder

The most recent video coding standard, High Efficiency Video Coding (HEVC), is able to significantly improve the compression performance at the expense of a huge computational complexity increase with respect to its predecessor, H.264/AVC. Parallel versions of the HEVC encoder may help to reduce the overall encoding time in order to make it more suitable for practical applications. In this work, we study two parallelization strategies. One of them follows a coarse-grain approach, where parallelization is based on frames, and the other one follows a fine-grain approach, where parallelization is performed at subpicture level. Two different frame-based approaches have been developed. The first one only uses MPI and the second one is a hybrid MPI/OpenMP algorithm. An exhaustive experimental test was carried out to study the performance of both approaches in order to find out the best setup in terms of parallel efficiency and coding performance. Both frame-based and subpicture-based approaches are compared under the same hardware platform. Although subpicture-based schemes provide an excellent performance with high-resolution video sequences, scalability is limited by resolution, and the coding performance worsens by increasing the number of processes. Conversely, the proposed frame-based approaches provide the best results with respect to both parallel performance (increasing scalability) and coding performance (not degrading the rate/distortion behavior).

A Perceptual Encryption Scheme for HEVC Video with Lossless Compression

Aiming to protect the video content and facilitate online video consumption, a perceptual encryption scheme is proposed for high efficiency video coding (HEVC) video. Based on RC4 algorithm, a key stream generation method is constructed, whose proportion of “1” and “0” can be regulated. During HEVC encoding, four kinds of syntax elements including motion vector difference (MVD)' sign, MVD's amplitude, sign of the luma residual coefficient and sign of the chroma residual coefficient, are encrypted by the regulated key stream. Experimental results and analysis show that the proposed scheme has good perceptual protection for the video content, and some advantages such as low computational cost, format-compliance and no bitrate increase can be achieved. It provides an effective resolution for the paid video-on-demand services.

A Reversible Information Hiding Method Based on HEVC

With the rapid development of agricultural information technology, the security of agricultural information data has become a hot issue. The safety of ensuring the transmission of important agricultural information on the Internet in agricultural informatization was studied in this paper. By hiding the content and existence of information, the purpose of secure transmission of information can be achieved. HEVC (High-Efficiency Video Coding), the latest video coding standard jointly developed for ISO/IEC and ITU-T. An optimized differential expansion information hiding method based on HEVC video is proposed. In order to enable the algorithm achieving large-capacity steganography and restoring the original video without distortion, the motion vector coefficient pair is taken as the carrier, the information hiding is performed by reducing the difference expansion coefficient. And the least significant bit of the motion vector after steganography is replaced by the secret information to achieve double embedding. On the extraction side, after the complete extraction of information, the original video can be restored without distortion. Experimental results show that this method is compared with the difference expansion method, the PSNR of the video after steganography is increased by 4db, and the bit rate is reduced by 0.7. It can be seen that this method has good visual imperceptibility. It is important that the embedded capacity has been increased by nearly 35% than DE method. The purpose of large capacity steganography is achieved. In the extraction end, the embedded secret information can be accurately extracted and the original video can be recovered without distortion. This is of great significance for the secure transmission of important agricultural information.

IF-RD optimisation for bandwidth compression in video HEVC and congestion control in wireless networks using dolphin echolocation optimisation with FEC

At present, the latest standard for coding the videos is high-efficiency video coding (HEVC) technique. Owing to limitations of wireless channels on time variability and bandwidth, video transmission to multiple mobile users is difficult. Inter frame-rate distortion (IF-RD) is the technique used in this paper, and it provides more clear videos with a reduction in motion signal by compressing bandwidth and enhancing optimisation in HEVC. First, the multi-resolution encoder encodes the video by employing a fusion strategy called IF-RD optimisation strategy. In order to improve performance and achieve noiseless transmission, the forward error correction (FEC) and dolphin echolocation optimisation techniques are integrated. Token-based congestion control (TBCC) reduces messages that are dropped due to congestion in the network. It also provides computation time. By adopting HEVC, the system performs well and achieves better compression in bandwidth and saves better Peak signal-to-noise ratio (PSNR) data rate with no extra time for encoding.

A Perceptual Video Coding Based on JND Model

In view of the fact that the current high efficiency video coding standard does not consider the characteristics of human vision, this paper proposes a perceptual video coding algorithm based on the just noticeable distortion model (JND). The adjusted JND model is combined into the transformation quantization process in high efficiency video coding (HEVC) to remove more visual redundancy and maintain compatibility. First of all, we design the JND model based on pixel domain and transform domain respectively, and the pixel domain model can give the JND threshold more intuitively on the pixel. The transform domain model introduces the contrast sensitive function into the model, making the threshold estimation more precise. Secondly, the proposed JND model is embedded in the HEVC video coding framework. For the transformation skip mode (TSM) in HEVC, we adopt the existing pixel domain called nonlinear additively model (NAMM). For the non-transformation skip mode (non-TSM) in HEVC, we use transform domain JND model to further reduce visual redundancy. The simulation results show that in the case of the same visual subjective quality, the algorithm can save more bitrates.

Efficient HEVC selective stream encryption using chaotic logistic map

At present, the digital video encryption technology has become an interest research topic as a result of very rapid evolution in the application of real-time video over the Internet. So this paper presents a new method for encrypting the selective sensitive data of the latest video coding standard, which called High-Efficiency Video Coding (HEVC). The High-Efficiency Video Coding was founded in 2013 by the Joint Collaborative Team on Video Coding (JCT-VC) from the ISO/IEC Moving Picture Experts Group (MPEG) and ITU-T Video Coding Experts Group (VCEG). The proposed selective encryption HEVC video technique uses the low complexity overhead chaotic logistic map (CLM) to encrypt the sign bits of the Motion Vector Difference (MVD) and the Discrete Cosine Transform (DCT) coefficients in the entropy stage of the process of video encoding. The contribution of the proposed CLM-based HEVC SE is to encrypt the sensitive video bits with the features of low complexity overhead, fast encoding time, keeping the HEVC constant bitrate and format compliant. Also, this paper introduces a comparative study between the proposed CLM-based HEVC SE and the Glenn HEVC SE that uses the Advanced Encryption Standard (AES). Experimental results demonstrate the main feature of the proposed CLM-based HEVC SE, which turned out to save the time of the video encoding with remaining of the near visual distortion of the encrypted video stream by Glenn HEVC SE. This feature is due to the low complexity of the CLM-based encryption employed in the proposed CLM-based HEVC SE scheme instead of using the AES in the Glenn HEVC SE. A course of security investigation experiments is performed for the proposed CLM-based HEVC SE including the main security performance metrics like encryption quality, key space, statistical and sensitivity tests. The achieved test results ensured the superiority of the proposed CLM-based HEVC SE for digital video streams.