265 Video Research Articles

Uncertainty of digital image correlation under video compression and DSP optimization.

The storage and transmission of videos at high spatial resolution remain a great challenge in image-based optical techniques. The uncertainty of digital image correlation (DIC) was assessed following speckle video compression under High Efficiency Video Coding (HEVC/H.265). First, the evaluation criterion for the DIC accuracy affected by compression was provided. The stability of H.265 video compression in DIC was studied considering different compressed frames under different target quantization parameters (QPs) and compression ratios (CRs). The deformation uncertainty of the DIC itself as affected by H.265 video compression was further investigated through uniform translation and non-uniform sinusoidal deformation performance. Moreover, the optimized digital speckle pattern (DSP) was re-evaluated considering video compression-induced uncertainty. DSPs with parameters of different diameters and randomness were compressed using various QPs and CRs. In addition, DSP evaluation was performed under both translation and non-homogeneous deformation conditions. The feasibility of the re-optimized DSP under H.265 video compression was validated using a defective bending beam, and DSP videos with a speckle size of 8 pixels reached a high CR within an acceptable margin of error.

Performance Analysis and Energy Consumption of H.264 and H.265 Video Coding Standards

Performance Analysis and Energy Consumption of H.264 and H.265 Video Coding Standards

ICatcher+: Robust and Automated Annotation of Infants' and Young Children's Gaze Behavior From Videos Collected in Laboratory, Field, and Online Studies.

Technological advances in psychological research have enabled large-scale studies of human behavior and streamlined pipelines for automatic processing of data. However, studies of infants and children have not fully reaped these benefits because the behaviors of interest, such as gaze duration and direction, still have to be extracted from video through a laborious process of manual annotation, even when these data are collected online. Recent advances in computer vision raise the possibility of automated annotation of these video data. In this article, we built on a system for automatic gaze annotation in young children, iCatcher, by engineering improvements and then training and testing the system (referred to hereafter as iCatcher+) on three data sets with substantial video and participant variability (214 videos collected in U.S. lab and field sites, 143 videos collected in Senegal field sites, and 265 videos collected via webcams in homes; participant age range = 4 months-3.5 years). When trained on each of these data sets, iCatcher+ performed with near human-level accuracy on held-out videos on distinguishing "LEFT" versus "RIGHT" and "ON" versus "OFF" looking behavior across all data sets. This high performance was achieved at the level of individual frames, experimental trials, and study videos; held across participant demographics (e.g., age, race/ethnicity), participant behavior (e.g., movement, head position), and video characteristics (e.g., luminance); and generalized to a fourth, entirely held-out online data set. We close by discussing next steps required to fully automate the life cycle of online infant and child behavioral studies, representing a key step toward enabling robust and high-throughput developmental research.

Modified Cuckoo Search Algorithm for Motion Vector Estimation

Motion estimation and motion compensation are the accepted process in H.264 and H.265 video coding standard to reduce temporal redundancy. Several fast block matching algorithms have been developed to reduce the calculation cost in the motion estimation process. But quick block matching algorithms often lead to a local minimum. Several researchers used different population-based nature-inspired algorithms to perform block matching. Algorithms like genetic algorithm, differential evolution, particle swarm optimization were used in numerous motion estimation algorithms. Different algorithms used a fitness approximation strategy to reduce computation cost. Jaya algorithm-based block matching is the most efficient block matching algorithm in the available literature. Jaya algorithm is free from algorithmic specific parameter which speeds up the process. This article proposes a few modifications to the traditional cuckoo search algorithm and then, a block matching algorithm was proposed based on the modified cuckoo search algorithm. Fitness approximation, adaptive termination, and zero motion prejudgment modules were used with the modified cuckoo search algorithm to reduce the number of redundant calculations. The performance of the proposed algorithm was compared with the exhaustive search algorithm and other benchmarking algorithms in terms of Peak Signal to Noise Ratio (PSNR), Structure Similarity Index (SSIM), and average search point required to calculate a motion vector for a block. The proposed algorithm delivers better performance compared to the benchmarking algorithms.

H.264 and H.265 video traffic modeling using neural networks

As video has become the dominant type of traffic over wired and wireless networks, the efficient transmission of video streams is of paramount importance. Hence, especially for wireless networks, the optimum utilization of the available bandwidth while preserving the users’ Quality of Service and Quality of Experience requirements is crucial. Towards this goal, the accurate prediction of upcoming video frame sizes can play a significant role. This work focuses on achieving such an accurate prediction for videos encoded with H.264 and H.265, which are the major state-of-the-art standards based on their current market share. Unlike previous studies, we use single-step and multi-step approaches to capture the long-range dependence and short-range dependence properties of variable bit rate video traces through neural networks-based modeling. We evaluate the accuracy of Long Short Term Memory, Convolutional Neural Networks and Sequence-to-Sequence models and compare them with existing approaches. Our models show significantly higher accuracy for a variety of videos. We also provide a case study on how our model can be used for traffic policing purposes.

Averting BER Floor with Iterative Source and Channel Decoding for Layered Steered Space-Time Codes.

The widespread development in wireless technologies and the advancements in multimedia communication have brought about a positive impact on the performance of wireless transceivers. We investigate the performance of our three-stage turbo detected system using state-of-the-art high efficiency video coding (HEVC), also known as the H.265 video standard. The system makes use of sphere packing (SP) modulation with the combinational gain technique of layered steered space-time code (LSSTC). The proposed three-stage system is simulated for the correlated Rayleigh fading channel and the bit-error rate (BER) curve obtained after simulation is free of any floor formation. The system employs low complexity source-bit coding (SBC) for protecting the H.265 coded stream. An intermediate recursive unity-rate code (URC) with an infinite impulse response is employed as an inner precoder. More specifically, the URC assists in the prevention of the BER floor by distributing the information across the decoders. There is an observable gain in the BER and peak signal-to-noise ratio (PSNR) performances with the increasing value of minimum Hamming distance () using the three-stage system. Convergence analysis of the proposed system is investigated through an extrinsic information transfer (EXIT) chart. Our proposed system demonstrates better performance of about 22 dB than the benchmarker utilizing LSSTC-SP for iterative source-channel detection, but without exploiting the optimized SBC schemes.

On the Performance of Video Resolution, Motion and Dynamism in Transmission Using Near-Capacity Transceiver for Wireless Communication.

This article investigates the performance of various sophisticated channel coding and transmission schemes for achieving reliable transmission of a highly compressed video stream. Novel error protection schemes including Non-Convergent Coding (NCC) scheme, Non-Convergent Coding assisted with Differential Space Time Spreading (DSTS) and Sphere Packing (SP) modulation (NCDSTS-SP) scheme and Convergent Coding assisted with DSTS and SP modulation (CDSTS-SP) are analyzed using Bit Error Ratio (BER) and Peak Signal to Noise Ratio (PSNR) performance metrics. Furthermore, error reduction is achieved using sophisticated transceiver comprising SP modulation technique assisted by Differential Space Time Spreading. The performance of the iterative Soft Bit Source Decoding (SBSD) in combination with channel codes is analyzed using various error protection setups by allocating consistent overall bit-rate budget. Additionally, the iterative behavior of SBSD assisted RSC decoder is analyzed with the aid of Extrinsic Information Transfer (EXIT) Chart in order to analyze the achievable turbo cliff of the iterative decoding process. The subjective and objective video quality performance of the proposed error protection schemes is analyzed while employing H.264 advanced video coding and H.265 high efficient video coding standards, while utilizing diverse video sequences having different resolution, motion and dynamism. It was observed that in the presence of noisy channel the low resolution videos outperforms its high resolution counterparts. Furthermore, it was observed that the performance of video sequence with low motion contents and dynamism outperforms relative to video sequence with high motion contents and dynamism. More specifically, it is observed that while utilizing H.265 video coding standard, the Non-Convergent Coding assisted with DSTS and SP modulation scheme with enhanced transmission mechanism results in gain of 20 dB with reference to the Non-Convergent Coding and transmission mechanism at the objective PSNR value of 42 dB. It is important to mention that both the schemes have employed identical code rate. Furthermore, the Convergent Coding assisted with DSTS and SP modulation mechanism achieved superior performance with reference to the equivalent rate Non-Convergent Coding assisted with DSTS and SP modulation counterpart mechanism, with a performance gain of 16 dB at the objective PSNR grade of 42 dB. Moreover, it is observed that the maximum achievable PSNR gain through H.265 video coding standard is 45 dB, with a PSNR gain of 3 dB with reference to the identical code rate H.264 coding scheme.

An effective and secure video watermarking using hybrid technique

Now, all satellite channels handle high-quality data, including HD video files (1 K, 2 K, and 4 K). High-quality compression software is required to archive and transmit these files accurately and efficiently. HEVC is a standard development technique for high-quality video compression which can produce double compression while preserving video quality. On the other hand, the use of a robust digital video watermark algorithm can solve copyright issues for these types of categories. Therefore, in this paper, an efficient compression-based secure digital watermarking is proposed. In this paper, initially, the video are converted into number of frames. Then, we de-compose the frame using dual-tree complex wavelet transform. After that, to increase the security of the system, the embedding positions are optimally selected using adaptive cuttlefish optimization algorithm. Then, the secrete images are encrypted using elliptic curve cryptography algorithm. After that, the encrypted images are converted into binary bit. Then, the binary bits are embedded into the selected position of video frame. After the encryption process, to decreases the size of encrypted document, H.265 video encoding approach is applied. This method is, effectively, reduce the size of the image, without affecting quality of the image. Finally, the compressed image is transmitted to the receiver. The reverse process of embedding is used for extraction process. The performance of proposed approach is analyzed in terms of different metrics and effectiveness compared with different methods.

Pengiriman Video secara Live Streaming Menggunakan Dynamic Adaptive Streaming over HTTP (DASH)

Keterbatasan bandwidth dan fluktuasi trafik pada jaringan menjadi kendala dalam proses pengiriman video. Pada saat ketersediaan bandwidth kecil dan traffic jaringan yang tinggi, proses pengiriman video akan memakan waktu yang lama dikarenakan proses transmisi video yang lambat atau lebih umum disebut dengan buffering. Penelitian ini melakukan evaluasi pengiriman video secara live streaming menggunakan metode Dynamic Adaptive Streaming over HTTP (DASH) pada jaringan LAN. DASH merupakan sebuah protokol streaming adaptive yang mampu menyajikan video dengan kualitas video sesuai kemampuan jaringan pada klien. Implementasi ini dilakukan menggunakan video kompresi H.265 dan proses streaming dilakukan pada jaringan LAN secara live streaming sebanyak 20 klien. Hasil penelitian ini diperoleh nilai throughput pengiriman video mencapai 1,4 Mbps dan nilai delay terbesar 12,5 ms. Persentase permintaan klien terhadap kualitas video tertinggi untuk 1 klien sebanyak 98%. Sedangkan penggunaan 20 klien, permintaan untuk video kualitas tinggi berkurang menjadi 46% yang membuktikan bahwa DASH berhasil diimplementasikan secara live streaming.
 Kata kunci: Video, Live, Streaming, H.265, DASH

Speed-Distortion Optimization: Tradeoffs in Open-Source HEVC Encoding

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">The high-efficiency video coding (HEVC) video compression standard, which drives a significant increase in coding efficiency, is an essential technology for delivering ultrahigh-definition content in the high dynamic range (HDR). This improved coding efficiency comes at a significant cost in computational complexity. Adaptive streaming and content-adaptive encoding significantly increase the compute required for encoding for the additional encodes and analysis required to support the corresponding use cases. All these factors combined require a careful analysis of tradeoffs to avoid exorbitant infrastructure costs of transition to HEVC. This paper discusses how the throughput of an HEVC encoder can be optimized to enable a cost-efficient distributed encoding system running on commodity hardware. We chose the popular open-source ×265 video encoder for this study due to its wide adoption. We first examine the ×265 presets, which combine various performance and encoding efficiency tradeoffs into a single operational point. We then detail some additional options that enable additional analysis on a selective subset of cases, such as per frame or per coding tree unit; these options are representative of several such options that are not exposed via the presets of ×265. Specifically, we discuss options pertaining to selective in-loop filtering and dynamically retargeting rate-distortion optimization (RDO) tools depending on the quality fluctuations encountered at runtime. We present tradeoff results for real-world 4K HDR content to demonstrate the applicability of these coding tools to real content used for over-the-top (OTT) and live streaming</i> .

Scalable Virtual Network Video-Optimizer for Adaptive Real-Time Video Transmission in 5G Networks

The increasing popularity of video applications and ever-growing high-quality video transmissions (e.g., 4K resolutions), has encouraged other sectors to explore the growth of opportunities. In the case of health sector, mobile Health services are becoming increasingly relevant in real-time emergency video communication scenarios where a remote medical experts’ support is paramount to a successful and early disease diagnosis. To minimize the negative effects that could affect critical services in a heavily loaded network, it is essential for 5G video providers to deploy highly scalable and priorizable in-network video optimization schemes to meet the expectations of a large quantity of video treatments. This paper presents a novel 5G Video Optimizer Virtual Network Function (vOptimizerVNF) that leverages the latest technologies in 5G and video processing to address this important challenge. Advanced traffic filtering is coupled with Scalable H.265 video coding to enable run-time bandwidth-saving video optimization without compromising Quality of Service (QoS); kernel-space video processing is introduced to achieve further performance gains; and the use of a Virtual Network Function (VNF) facilitates dynamic deployment of virtualized video optimizers to achieve scalability and flexibility in this service. The proposed approach is implemented in a realistic 5G testbed and empirical results demonstrate the superior scalability and performance achieved.

Mitigation of H.264 and H.265 Video Compression for Reliable PRNU Estimation

The photo-response non-uniformity (PRNU) is a distinctive image sensor characteristic, and an imaging device inadvertently introduces its sensor's PRNU into all media it captures. Therefore, the PRNU can be regarded as a camera fingerprint and used for source attribution. The imaging pipeline in a camera, however, involves various processing steps that are detrimental to PRNU estimation. In the context of photographic images, these challenges are successfully addressed and the method for estimating a sensor's PRNU pattern is well established. However, various additional challenges related to generation of videos remain largely untackled. With this perspective, this work introduces methods to mitigate disruptive effects of widely deployed H.264 and H.265 video compression standards on PRNU estimation. Our approach involves an intervention in the decoding process to eliminate a filtering procedure applied at the decoder to reduce blockiness. It also utilizes decoding parameters to develop a weighting scheme and adjust the contribution of video frames at the macroblock level to PRNU estimation process. Results obtained on videos captured by 28 cameras show that our approach increases the PRNU matching metric up to more than five times over the conventional estimation method tailored for photos.

Five-stage pipelined dual-edge deblocking filter architecture for H.265 video codec

Five-stage pipelined dual-edge deblocking filter architecture for H.265 video codec

Video steganography: A review

Video steganography is becoming an important research area in various data hiding technologies, which has become a promising tool because not only the security requirement of secret message transmission is becoming stricter but also video is more favored. In this paper, according to the embedded position of secret message, video steganography is divided into three categories: intra-embedding, pre-embedding and post-embedding. Intra-embedding methods are categorized according to the video compression stages such as intra-prediction, motion vectors, pixels interpolation, transform coefficients. Pre-embedding methods are manipulated on the raw video, which can be classified into spatial and transform domains. Post-embedding methods are mainly focused on the bitstreams, which means the procedure of embedding and extraction of video steganography are all manipulated on the compressed bit stream. Then we introduce the performance assessment for video steganography and the future popular video steganography including H.265 video steganography, robust video steganography and reversible video steganography. And challenges are finally discussed in this paper.

5G-QoE: QoE Modelling for Ultra-HD Video Streaming in 5G Networks

Traffic on future fifth-generation (5G) mobile networks is predicted to be dominated by challenging video applications such as mobile broadcasting, remote surgery and augmented reality, demanding real-time, and ultra-high quality delivery. Two of the main expectations of 5G networks are that they will be able to handle ultra-high-definition (UHD) video streaming and that they will deliver services that meet the requirements of the end user’s perceived quality by adopting quality of experience (QoE) aware network management approaches. This paper proposes a 5G-QoE framework to address the QoE modeling for UHD video flows in 5G networks. Particularly, it focuses on providing a QoE prediction model that is both sufficiently accurate and of low enough complexity to be employed as a continuous real-time indicator of the “health” of video application flows at the scale required in future 5G networks. The model has been developed and implemented as part of the EU 5G PPP SELFNET autonomic management framework, where it provides a primary indicator of the likely perceptual quality of UHD video application flows traversing a realistic multi-tenanted 5G mobile edge network testbed. The proposed 5G-QoE framework has been implemented in the 5G testbed, and the high accuracy of QoE prediction has been validated through comparing the predicted QoE values with not only subjective testing results but also empirical measurements in the testbed. As such, 5G-QoE would enable a holistic video flow self-optimisation system employing the cutting-edge Scalable H.265 video encoding to transmit UHD video applications in a QoE-aware manner.

Wavelet-based frame video coding algorithms using fovea and SPECK

Current video coding standards such as the H.264 or Advanced Video Coding (AVC) and the H.265 or High Efficiency Video Coding (HEVC) are based on the Integer Discrete Cosine Transform (IDCT). However, it has been shown that wavelet-based algorithms have better performance than IDCT-based algorithms for still images. Also, exploiting the human visual system characteristics in stationary point of view image and video transmissions like the fovea aliasing can improve the quality of the reconstructed image. In this paper, two wavelet-based video coding approaches called SPECK-based Codec (SP-Codec) and Adaptive Wavelet/Fovea-based Codec (AWFV-Codec) are proposed. The proposed SP-Codec approach applies the Set Partitioned Embedded Block Codec (SPECK) wavelet-based compression algorithm in order to increase the intra-frame coding quality. The second proposed approach AWFV-Codec uses the Adaptive Fovea Set Partitioned Embedded Block Codec (AFV-SPECK) fovea wavelet-based compression algorithm for intra-frame coding. Fovea based compression allows to increase the quality of the reconstructed frames over regions of interest (ROI). A comparison of the proposed algorithms against the HEVC based on IDCT approach shows how the proposed wavelet-based schemes achieve higher compression ratios and higher reconstruction quality. When fixation point of view is stationary, the proposed wavelet/fovea-based algorithm achieves better quality at lower compression ratios than the wavelet-based only proposed algorithm.

Evaluation of H.265 Video Delivery Based on Dynamic Adaptive Streaming over HTTP (DASH) Using Mobile Devices

MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) is a standard for HTTP streaming that allows interoperability between servers and clients from different vendors which is able to adjust the speed of video delivery to changing bandwidth. Today there is the latest H.265 video coding known as the High Efficiency Video Coding (HEVC). This research implemented the delivery of the H.265 video through the method of Dynamic Adaptive Streaming over HTTP (DASH) using mobile devices. The test was conducted by sending videos over 3G networks with GSM length video segment consists of 2 seconds, 5 seconds, 10 seconds and 20 seconds. The video quality provided in this study consisted of 5 video levels with different bit rates. From the test results, the submitted videos using a smaller video segment generated greater throughput and acquired more video quality with a higher bit rate than the video to a larger segment. Video delivery with segment of 2 seconds acquired video quality with the highest level of 83%, meanwhile the video delivery segment of 20 seconds obtained video quality with the highest level of 33%.

Energy-aware cache hierarchy assessment targeting HEVC encoder execution

This article presents a framework for assessing the behavior and energy impact of cache hierarchies when encoding HEVC on general-purpose processors. The memory energy estimation framework estimates energy consumption of cache hierarchies based on mathematical models combined with memory access profiling tools. The energy analysis of several cache hierarchies targeting HEVC encoders with different input parameters is also carried out. This article provides relevant information on the energy consumption of HEVC encoders by taking into account the different tradeoffs between energy efficiency, coding efficiency, and other important cache memory design parameters, such as miss rates and access latency. The first analysis explores cache performance for different specifications, such as capacity, line size. Results show that most of the energy is spent on reading operations (almost 73% on the first level cache), indicating that HEVC encoders could benefit from memory technologies with low reading energy costs. This analysis also pointed that increasing the capacity affects more the energy performance of the first level cache, which represents 34.78% (on average) more energy consumption than the last level cache. Based on this investigation, we report the most suited cache specifications for HEVC encoders for each video resolution. The second analysis discusses the impact of HEVC input parameters in cache performance, demonstrating that it is possible to save up to 30% of energy with a small increase of 2% in BD-BR. A comparative analysis between HM (HEVC model) and x265 (H.265 video codec) HEVC software models is presented, demonstrating that x265 is faster (speedup to 648x), and more cache efficient providing less memory energy (31.38% on average) compared to the HM implementation. The results obtained with the proposed framework indicate that the management of video encoding parameters combined with application-tuned cache specifications has a high potential to reduce energy consumption of video coding systems while keeping video quality.

An improved adaptive selection search for block motion estimation

Motion estimation has an important effect in H.265 video coding systems because it occupies a large amount of time in encoding system. So the quality of motion search selection affects the entire encoding efficiency directly. In this paper, a novel search algorithm which utilises an adaptive hexagon and small diamond search is proposed to overcome the drawbacks of the traditional block matching selection implemented in most current video coding standards. The adaptive search algorithm is chosen according to the motion strength of the current block. When the block is in active motion, the hexagon search provides an efficient search method; when the block is inactive, the small diamond search is adopted. Experimental simulation results showed that our adaptive search algorithm can speed up the search process with little effect on distortion performance compared with other traditional approaches.

An improved adaptive selection search for block motion estimation

Motion estimation has an important effect in H.265 video coding systems because it occupies a large amount of time in encoding system. So the quality of motion search selection affects the entire encoding efficiency directly. In this paper, a novel search algorithm which utilises an adaptive hexagon and small diamond search is proposed to overcome the drawbacks of the traditional block matching selection implemented in most current video coding standards. The adaptive search algorithm is chosen according to the motion strength of the current block. When the block is in active motion, the hexagon search provides an efficient search method; when the block is inactive, the small diamond search is adopted. Experimental simulation results showed that our adaptive search algorithm can speed up the search process with little effect on distortion performance compared with other traditional approaches.