scholarly journals Data Embedding in SHVC Video Using Threshold-Controlled Block Splitting

2021 ◽  
Vol 11 (11) ◽  
pp. 4850
Author(s):  
LieLin Pang ◽  
KokSheik Wong ◽  
Yiqi Tew ◽  
Susanto Rahardja
Keyword(s):  
Video Quality ◽  
Rate Distortion ◽  
Data Embedding ◽  
Video Content ◽  
Embedding Capacity ◽  
Bit Rate ◽  
Case Scenario ◽  
Splitting Technique ◽  
Prediction Mode ◽  
Few Data

With the increasing number of video applications, it is essential to resolve issues such as ineffective search of video content, tampered/forged video content, packet loss, to name a few. Data embedding is typically utilized as one of the solutions to address the aforementioned issues. One of the important requirements of data embedding is to maximize embedding capacity with minimal bit rate overhead while ensuring imperceptibility of the inserted data. However, embedding capacity varies depending on the video content and increasing the embedding capacity usually leads to video quality degradation. In this work, a threshold-controlled block splitting technique is proposed for embedding data into SHVC video. Specifically, the embedding capacity can be increased by coding the host video by using more small blocks, which can be achieved by tuning a threshold-controlled parameter in the rate distortion optimization process. Subsequently, the predictive syntax elements in both intra and inter-coded blocks are jointly utilized to embed data, which ensures that data can be embedded regardless of the prediction mode used in coding a block. Results suggest that the proposed method can achieve a trade-off between the increase in embedding capacity and bit rate overhead while maintaining video quality. In the best case scenario, the sequence PartyScene can embed 516.9 kbps with an average bit rate overhead of +7.0% for the Low Delay P configuration, while the same video can embed 1578.6 kbps with an average bit rate overhead of +2.9% for the All Intra configuration.

Binomial Bit-Rate Computation Model Based on Wireless Channel

2012 ◽  
Vol 241-244 ◽  
pp. 2482-2486
Author(s):  
Wei Ming Yang ◽  
Jian Zhang ◽  
Jin Xiang Peng
Keyword(s):  
Solution Method ◽  
Rate Distortion ◽  
Wireless Channel ◽  
Video Communication ◽  
Bit Allocation ◽  
Bit Rate ◽  
Computation Model ◽  
Refresh Rate ◽  
Network Bandwidth ◽  
Inter Frame

For the encoding bit-rate problem in H.264 wireless video communication, the bit-rate computation model and the standard deviation distortion model were analyzed to establish the relation between the quantization parameter of encoding bit-rate and the intra-frame refresh rate of macroblocks, a new proposal of the coding rate thus put forward based on the general binomial computation model theory. Furthermore, this method not only can adaptively adjust the bit allocation and quantization parameters to prevent buffer from overflowing downward or upward under given network bandwidth, but also can apply the rate-distortion to perfect the solution method, control the encoding bits accurately and optimize the allocation between the inter-frame encoding macroblocks.

A Research of Intra Prediction Coding with Variance of Prediction Mode Number

2015 ◽  
Vol 719-720 ◽  
pp. 1177-1183
Author(s):  
Wei Zheng ◽  
Long Ye ◽  
Jing Ling Wang ◽  
Qin Zhang
Keyword(s):  
State Of The Art ◽  
Intra Prediction ◽  
Mode Number ◽  
Bit Rate ◽  
Rate Reduction ◽  
Directional Information ◽  
Mode Index ◽  
Residual Image ◽  
Prediction Mode ◽  
Direction Information

Intra prediction is a key step in H.264/AVC to improve the coding performance with the idea that removing the directional redundancy among neighboring blocks. In order to cover more directional information existed in the image frames, there are usually many prediction modes can be selected in the state-of-the-art coding frameworks, but more bits are also needed to encode the prediction mode index information, then how to achieve the maximum overall bit-rate reduction became a problem. In this paper, 16 kinds of prediction modes are adopted by considering the direction information for 8x8 image blocks. Through calculating the bit-rate both for the mode index and residual image under different number of prediction modes, we obtain the most suitable prediction mode number relatively from the graphs. Experimental results show that, with the increase of prediction mode number, the residual information decreases obviously, and the sum of residual information and prediction mode index information also decreases but levels off after reaching a certain mode number, even has an obviously rising trend.

scholarly journals A Distortion-Free Data Hiding Scheme for Triangular Meshes Based on Recursive Subdivision

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yuan-Yu Tsai
Keyword(s):  
Principal Component Analysis ◽  
Data Hiding ◽  
Similarity Transformation ◽  
Principal Component ◽  
Secret Message ◽  
Subdivision Scheme ◽  
Data Embedding ◽  
Embedding Capacity ◽  
Free Data ◽  
Reversible Data Embedding

This study adopts a triangle subdivision scheme to achieve reversible data embedding. The secret message is embedded into the newly added vertices. The topology of added vertex is constructed by connecting it with the vertices of located triangle. For further raising the total embedding capacity, a recursive subdivision mechanism, terminated by a given criterion, is employed. Finally, a principal component analysis can make the stego model against similarity transformation and vertex/triangle reordering attacks. Our proposed algorithm can provide a high and adjustable embedding capacity with reversibility. The experimental results demonstrate the feasibility of our proposed algorithm.

Fuzzy Holoentropy-Based Adaptive Inter-Prediction Mode Selection for H.264 Video Coding

2019 ◽  
Vol 10 (2) ◽  
pp. 42-60
Author(s):  
Srinivas Bachu ◽  
N. Ramya Teja
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Performance ◽  
Mode Selection ◽  
Rate Distortion ◽  
Computation Time ◽  
Exhaustive Search ◽  
Inter Prediction ◽  
Major Drawback ◽  
Prediction Mode

Due to the advancement of multimedia and its requirement of communication over the network, video compression has received much attention among the researchers. One of the popular video codings is scalable video coding, referred to as H.264/AVC standard. The major drawback in the H.264 is that it performs the exhaustive search over the interlayer prediction to gain the best rate-distortion performance. To reduce the computation overhead due to exhaustive search on mode prediction process, this paper presents a new technique for inter prediction mode selection based on the fuzzy holoentropy. This proposed scheme utilizes the pixel values and probabilistic distribution of pixel symbols to decide the mode. The adaptive mode selection is introduced here by analyzing the pixel values of the current block to be coded with those of a motion compensated reference block using fuzzy holoentropy. The adaptively selected mode decision can reduce the computation time without affecting the visual quality of frames. Experimentation of the proposed scheme is evaluated by utilizing five videos, and from the analysis, it is evident that proposed scheme has overall high performance with values of 41.367 dB and 0.992 for PSNR and SSIM respectively.

scholarly journals Improved Coefficient Recovery and Its Application for Rewritable Data Embedding

2021 ◽  
Vol 7 (11) ◽  
pp. 244
Author(s):  
Alan Sii ◽  
Simying Ong ◽  
KokSheik Wong
Keyword(s):  
Image Coding ◽  
Rate Distortion ◽  
Divide And Conquer ◽  
Storage Device ◽  
Data Embedding ◽  
Discrete Cosine Transformation ◽  
Recovery Method ◽  
Embedding Method ◽  
Coefficient Recovery ◽  
Recovery Methods

JPEG is the most commonly utilized image coding standard for storage and transmission purposes. It achieves a good rate–distortion trade-off, and it has been adopted by many, if not all, handheld devices. However, often information loss occurs due to transmission error or damage to the storage device. To address this problem, various coefficient recovery methods have been proposed in the past, including a divide-and-conquer approach to speed up the recovery process. However, the segmentation technique considered in the existing method operates with the assumption of a bi-modal distribution for the pixel values, but most images do not satisfy this condition. Therefore, in this work, an adaptive method was employed to perform more accurate segmentation, so that the real potential of the previous coefficient recovery methods can be unleashed. In addition, an improved rewritable adaptive data embedding method is also proposed that exploits the recoverability of coefficients. Discrete cosine transformation (DCT) patches and blocks for data hiding are judiciously selected based on the predetermined precision to control the embedding capacity and image distortion. Our results suggest that the adaptive coefficient recovery method is able to improve on the conventional method up to 27% in terms of CPU time, and it also achieved better image quality with most considered images. Furthermore, the proposed rewritable data embedding method is able to embed 20,146 bits into an image of dimensions 512×512.

scholarly journals Texture Grouping and Statistical Optimization Based Mode Prediction Decision Algorithm for Fast HEVC Intra Coding

2021 ◽  
Author(s):  
Jianhua Wang ◽  
Feng Lin ◽  
Jing Zhao ◽  
Yongbing Long
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Rate Distortion ◽  
Statistical Optimization ◽  
Optimal Prediction ◽  
Statistical Probability ◽  
Decision Algorithm ◽  
Texture Information ◽  
Prediction Mode ◽  
Probability Optimization

Abstract HEVC (High Efficiency Video Coding), as one of the newest international video coding standard, can achieve about 50% bit rate reduction compared with H.264/AVC (Advanced Video Coding) at the same perceptual quality due to the use of flexible CTU(coding tree unit) structure, but at the same time, it also dramatically adds the higher computational complexity for HEVC. With the aim of reducing the computational complexity, a texture grouping and statistical optimization based mode prediction decision algorithm is proposed for HEVC intra coding in this paper. The contribution of this paper lies in the fact that we successfully use the texture information grouping and statistical probability optimization technology to rapidly determine the optimal prediction mode for the current PU, which can reduce many unnecessary prediction and calculation operations of HCost (Hadamard Cost) and RDCost (Rate Distortion Cost) in HEVC, thus saving much computation complexity for HEVC. Specially, in our scheme, firstly we group 35 intra prediction modes into 5 subsets of candidate modes list according to its texture information of edge in the current PU, and each subset only contains 11 intra prediction modes, which can greatly reduce many traversing number of candidate mode in RMD (Rough Mode Decision) from 35 to 11 prediction modes; Secondly we use the statistical probability of the first candidate modes in candidate modes list as well as MPM selected as the optimal prediction mode to reduce the number of candidate modes in RDO(Rate Distortion Optimization), which can reduce the number of candidate modes from 3+MPM or 8+MPM to 2 candidate modes; At last, we use the number of candidate modes determined above to quickly find the optimal prediction mode with the minimum RDCost by RDO process. As a result, the computational complexity of HEVC can be efficiently reduced by our proposed scheme. And the simulation results of our experiments show that our proposed intra mode prediction decision algorithm based on texture information grouping and statistical probability optimization in this paper can reduce about 46.13% computational complexity on average only at a cost of 0.67% bit rate increase and 0.056db PSNR decline compared with the standard reference HM16.1 algorithm.

Analyzing the Quality of Aesthetic Surgery Procedure Videos on TikTok

2021 ◽  
Author(s):  
Anjali Om ◽  
Bobby Ijeoma ◽  
Sara Kebede ◽  
Albert Losken
Keyword(s):  
Social Media ◽  
Breast Augmentation ◽  
Cosmetic Surgery ◽  
Video Quality ◽  
Aesthetic Surgery ◽  
Video Content ◽  
Medical Providers ◽  
Cosmetic Procedure ◽  
Different Content

Abstract Background TikTok is one of the most popular and fastest growing social media apps in the world. Previous studies have analyzed the quality of patient education information on older video platforms, but the quality of plastic and cosmetic surgery videos on TikTok has not yet been determined. Objectives To analyze the source and quality of certain cosmetic procedure videos on TikTok. Methods The TikTok mobile application was queried for content related to two popular face procedures (rhinoplasty and blepharoplasty) and two body procedures (breast augmentation and abdominoplasty). Two independent reviewers analyzed video content according to the DISCERN scale, a validated, objective criteria that assesses the quality of information on a scale of 1-5. Quality scores were compared between videos produced by medical and nonmedical creators and between different content categories. Results There were 4.8 billion views and 76.2 million likes across included videos. Videos were created by MDs (56%) and laypersons (44%). Overall average DISCERN score out of 5 corresponded to very poor video quality for rhinoplasty (1.55), blepharoplasty (1.44), breast augmentation (1.25) and abdominoplasty (1.29). DISCERN scores were significantly higher among videos produced by MDs than by laypersons for all surgeries. Comedy videos consistently had the lowest average DISCERN scores, while educational videos had the highest. Conclusions It is increasingly important that medical professionals understand the possibility of patient misinformation in the age of social media. We encourage medical providers to be involved in creating quality information on TikTok and educate patients about misinformation to best support health literacy.

GPU-Based MPEG-2 to Secure Scalable Video Transcoding

2014 ◽  
Vol 6 (2) ◽  
pp. 52-69
Author(s):  
Yueyun Shang ◽  
Dengpan Ye ◽  
Zhuo Wei ◽  
Yajuan Xie
Keyword(s):  
Graphics Processing Unit ◽  
Scalable Video Coding ◽  
Single Layer ◽  
Rate Distortion ◽  
Scalable Video ◽  
Processing Unit ◽  
Video Content ◽  
High Definition ◽  
Network Bandwidth ◽  
A Minor

Most of the high definition video content are still produced in a single-layer MPEG-2 format. Multiple-layers Scalable Video Coding (SVC) offers a minor penalty in rate-distortion efficiency when compared to single-layer coding MPEG-2. A scaled version of the original SVC bitstream can easily be extracted by dropping layers from the bitstream. This paper proposes a parallel transcoder from MPEG-2 to SVC video with Graphics Processing Unit (GPU), named PTSVC. The objective of the transcoder is to migrate MPEG-2 format video to SVC format video such that clients with different network bandwidth and terminal devices can seamlessly access video content. Meanwhile, the transcoded SVC videos are encrypted such that only authorized users can access corresponding SVC layers. Using various scalabilities SVC test sequences, experimental results on TM5 and JSVM indicate that PTSVC is a higher efficient transcoding system compared with previous systems and only causes little quality loss.

Per Clip Lagrangian Multiplier Optimisation for HEVC

2020 ◽  
Vol 2020 (10) ◽  
pp. 136-1-136-7
Author(s):  
Daniel J Ringis ◽  
François Pitié ◽  
Anil Kokaram
Keyword(s):  
Video Compression ◽  
Rate Distortion ◽  
Lagrangian Multiplier ◽  
Video Content ◽  
Compression Performance ◽  
Quality Video ◽  
Rate Improvement ◽  
Optimisation Methods ◽  
High Quality Video ◽  
The Impact

The majority of internet traffic is video content. This drives the demand for video compression in order to deliver high quality video at low target bitrates. This paper investigates the impact of adjusting the rate distortion equation on compression performance. An constant of proportionality, k, is used to modify the Lagrange multiplier used in H.265 (HEVC). Direct optimisation methods are deployed to maximise BD-Rate improvement for a particular clip. This leads to up to 21% BD-Rate improvement for an individual clip. Furthermore we use a more realistic corpus of material provided by YouTube. The results show that direct optimisation using BD-rate as the objective function can lead to further gains in bitrate savings that are not available with previous approaches.

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