Distributed Video Coding Codec Research Articles

Fast Side Information Generation for High-Resolution Videos in Distributed Video Coding Applications

Distributed video coding (DVC) is an attractive and promising scheme that suits the constrained video applications, such as wireless sensor networks or wireless surveillance systems. In DVC, estimation of fast and consistent side information (Տį) is a critical issue for instant and real-time decoding. This issue becomes even more serious for high-resolution videos. Therefore, to minimise the side information estimation computational complexity, in this work, a computationally low complex DVC codec is proposed, which uses a simple phase interpolation (Phase-I) algorithm. It performs faster for all resolutions videos, and significant results are achieved for high-resolution videos with a large group of pictures (GOP). For the proposed technique, the computation time rapidly decreases with an increase in resolution. It performs 221% to 280% faster from conventional frame interpolation method for high-resolution videos and large GOP at the cost of little degradation in the visual quality of estimated side information.

A Novel Consistent Quality Driven for JEM Based Distributed Video Coding

Distributed video coding (DVC) is an attractive and promising solution for low complexity constrained video applications, such as wireless sensor networks or wireless surveillance systems. In DVC, visual quality consistency is one of the most important issues to evaluate the performance of a DVC codec. However, it is the fact that the quality of the decoded frames that is achieved in most recent DVC codecs is not consistent and it is varied with high quality fluctuation. In this paper, we propose a novel DVC solution named Joint exploration model based DVC (JEM-DVC) to solve the problem, which can provide not only higher performance as compared to the traditional DVC solutions, but also an effective scheme for the quality consistency control. We first employ several advanced techniques that are provided in the Joint exploration model (JEM) of the future video coding standard (FVC) in the proposed JEM-DVC solution to effectively improve the performance of JEM-DVC codec. Subsequently, for consistent quality control, we propose two novel methods, named key frame quantization (KF-Q) and Wyner-Zip frame quantization (WZF-Q), which determine the optimal values of the quantization parameter (QP) and quantization matrix (QM) applied for the key and WZ frame coding, respectively. The optimal values of QP and QM are adaptively controlled and updated for every key and WZ frames to guarantee the consistent video quality for the proposed codec unlike the conventional approaches. Our proposed JEM-DVC is the first DVC codec in literature that employs the JEM coding technique, and then all of the results that are presented in this paper are new. The experimental results show that the proposed JEM-DVC significantly outperforms the relevant DVC benchmarks, notably the DISCOVER DVC and the recent H.265/HEVC based DVC, in terms of both Peak signal-to-noise ratio (PSNR) performance and consistent visual quality.

Efficient decoding algorithm for 3D video over wireless channels

In wireless communication networks, additive channel noise and time varying multipath fading are considered amongst the main challenges and these effects will bring significant quality degradation to the transmitted 2D/3D video streams. This paper presents an efficient decoding algorithm for Distributed Video Coding (DVC) for enhanced performance of colour and depth based 3D video over error prone wireless channels. The maximum a-posteriori (MAP) algorithm for turbo decoding is modified considering the effects of the channel errors on both Wyner-Ziv and key frame bit streams of colour and depth videos. The proposed codec is simulated using a W-CDMA wireless channel model and the results are analyzed to determine the effect of the modifications. The performance of the state-of-the-art H.264/AVC video codec is also presented for comparison under similar conditions. The results show that the proposed modifications provide a significant improvement in the DVC codec performance under unfavourable channel conditions for colour plus depth based 3D video.

Multi-resolution extreme learning machine-based side information estimation in distributed video coding

Context: Encoding of video frames in a traditional video coding architecture involves exhaustive computations due to the motion estimation (ME) task. Hence, it requires a considerable amount of computing aid, battery power, and resource memory. These codecs are not effective and reliable for applications like surveillance systems, wireless sensor networks, wireless camcorders, having scarcity in the availability of resources and computing ability. Therefore, in such scenarios, distributed video coding (DVC) represents a viable solution for power-constrained hand-held devices. DVC empowers the adaptability in distributing the complexity between the encoder and the decoder. Objective: Like any other building block, the decoder driven side information (SI) generation module plays a key role in a DVC codec. The efficacy of a DVC codec firmly relies on the quality of the SI generated at the decoder. SI is considered to be the facsimile of the original Wyner-Ziv (WZ) frame. Hence, the superior the quality of SI, improved is the efficiency of the codec. The primary objective of the present work is to enhance the quality of the SI frame so that the overall performance of the DVC is improved. To achieve this objective, this article deals with a hybrid SI generation scheme utilizing the principles of discrete wavelet transform (DWT) and extreme learning machine (ELM) algorithm in a transform domain-based DVC framework. Results: Exhaustive simulations have been carried out for some standard video sequences with the proposed and benchmark schemes. The proposed scheme is evaluated with respect to different performance metrics such as rate-distortion (RD), SI peak-signal-to-noise-ratio (PSNR) vs frame number, number of parity requests per SI frame, and so on. Experimental results and its analyses corroborate that the performance of the proposed technique surpasses as that of the benchmark schemes.

Decoder driven side information generation using ensemble of MLP networks for distributed video coding

This paper proposes an ensemble of multi-layer perceptron (MLP) networks for side information (SI) generation in distributed video coding (DVC). In the proposed scheme, both three-layer and four-layer MLP structures are used to form the ensemble model. The proposed model includes four sub-modules. The first sub-module involves the training of the individual networks. The second sub-module selects ‘M’ number of trained MLPs based on the mean square error (MSE) performance metric. Next, the third sub-module involves the testing phase of each of the selected MLPs. Finally, in the last sub-module, the overall ensemble SI is generated using a dynamically averaging (DA) method. The primary goal of this work is to minimize the estimation error between the SI and the corresponding Wyner-Ziv (WZ) frame so that the overall efficiency of DVC codec can be increased. The proposed scheme is evaluated with respect to different parameters such as Rate-Distortion (RD), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), and number of parity requests made per estimated frame. The evaluation indicates that the proposed ensemble model shows better generalization capabilities with improved PSNR (in dB) as compared to each of the individual selected networks. Additionally, the comparative analysis also exhibits that the proposed SI generation scheme generates better SI frames in comparison with the contemporary techniques. Further, using a statistical test, namely, ANOVA with significance level of 5%, it has been validated that the proposed technique yields a significant enhancement in the performance as compared to that of the benchmark schemes.

High performance and low complexity decoding light-weight video coding with motion estimation and mode decision at decoder

Light-weight video coding (LVC) follows distributed video coding (DVC) and designs to move computational complexity from the encoder to the decoder, thus making a low computational complexity encoder. In traditional video coding, the high computational complexity encoder algorithms, where motion estimation and mode decision, are the main transferred objects. In order to alleviate the computational burden, the proposed architecture adopts the Partial Boundary Matching Algorithm (PBMA) and four flexible types of mode decision at the decoder; this circumvents the traditional use of motion estimation and mode decision at the encoder. In simulation, the proposed architecture, Padding Block-based LVC, not only outperforms the state-of-the-art DVC (DISCOVER) codec by up to 4~5 dB but also significantly decreases decoder complexity to approximately one hundred times lower than that of the DISCOVER codec.

Efficient Real-Time Distributed Video Coding by Parallel Progressive Side Information Regeneration

Distributed video coding (DVC) provides a different compression paradigm that consists of lightweight encoder and complex decoder. This compression paradigm shed a light for nowadays mobile devices which equipped with limited battery and computing resources while the corresponding multimedia service is backed up by cloud computing infrastructures. After years of developing, the coding performance and the decoding speed of DVC are still facing serious challenges, for example, DVC’s rate-distortion (RD) performance is far behind the traditional prediction based video codec (e.g., H.264) and the required decoding complexity handicaps its value in practical usage. In order to meet these challenges, we propose an efficient real-time DVC framework with progressive side information regeneration by taking GPGPU-based parallel computing into account. The proposed system can resolve one of the achilles’ heels, i.e., the large group of picture scenario, of DVC codec with good RD performance and much improved decoding speed. The Bjontegaard Delta peak signal-to-noise ratio improvement of our system is up to 2.87 dB as compared with DISCOVER codec, which is also comparable with that of the state-of-the-art optical flow-based DVC codecs. The average decoding speed goes up to 22.44 frames per second (FPS) and even up to 76.35 FPS for Hall sequence. To the best of our knowledge, this is the first DVC codec which tackles the RD performance and the decoding speed issues simultaneously.

Distributed video coding: Assessing the HEVC upgrade

In the distributed video coding (DVC) context, predictive Intra coding plays an important role not only as one of the most meaningful (low encoding complexity) benchmarks but also as the adopted coding mode for the so-called key frames used in the most popular DVC architectures. While the first DVC codecs adopted the H.263 Intra codec to play this role, it became clear around 2005 that the (standard) Intra coding reference codec had evolved and should become the H.264/AVC Intra codec, which has been used since then by the DVC literature. However, while DVC solutions have been evolving since those times, also predictive video coding has evolved and a new predictive video coding standard has recently emerged, the High Efficiency Video Coding (HEVC) standard. To acknowledge this evolution and be fair with the predictive coding technology, the improved DVC solutions should now integrate and be compared with the improved and more relevant HEVC standard and not anymore with the H.264/AVC 10-year-old standard. In this context, this paper proposes to upgrade the DVC tools and benchmarking by adopting the HEVC Intra codec to take the role that the H.264/AVC Intra standard was previously playing. To assess the impact of this inevitable upgrade, an advanced, representative DVC solution has been adopted and its performance assessed and compared in the context of the H.264/AVC and HEVC standard frameworks. The compression efficiency and computational complexity experiments performed allow concluding that upgrading DVC solutions with HEVC Intra coding allows strengthening the DVC positioning in the video coding landscape. This conclusion highlights how the experiments performed in this paper are critical to define the new DVC status quo.

Adaptive mode decision with residual motion compensation for distributed video coding

Distributed video coding (DVC) is a coding paradigm that entails low complexity encoding by exploiting the source statistics at the decoder. To improve the DVC coding efficiency, this paper presents a novel adaptive technique for mode decision to control and take advantage of skip mode and intra mode in DVC initially proposed by Luong et al. in 2013. The adaptive mode decision (AMD) is not only based on quality of key frames but also the rate of Wyner–Ziv (WZ) frames. To improve noise distribution estimation for a more accurate mode decision, a residual motion compensation is proposed to estimate a current noise residue based on a previously decoded frame. The experimental results, integrating AMD in two efficient DVC codecs, show that the proposed AMD DVC significantly improves the rate distortion performance without increasing the encoding complexity. For a GOP size of 2 on the set of six test sequences, the average (Bjøntegaard) bitrate saving of the proposed codec is 35.5% on WZ frames compared with the DISCOVER codec. This saving is mainly achieved by AMD.

Correlation Noise-Based Unequal Error Protected Rate-Adaptive Codes for Distributed Video Coding

Distributed video coding (DVC) is a paradigm that can shift most of the computational intensive tasks from the encoder to the decoder. This allows for the design of low complexity encoders that can be deployed in devices equipped with limited resources. However, the compression efficiency obtained using practical DVC codecs are still distant from those of traditional predictive video coding schemes such as H.264/AVC. One of the limitations of the existing DVC architectures is that they consider the correlation noise to be randomly distributed across the whole video frame. This paper shows that the Syner–Ziv (WZ) values that are closer to the endpoints of the quantization intervals have a higher probability of producing incorrect side information (SI) predictions. Thus, through this knowledge, rate-adaptive low-density parity-check accumulate codes that provide a higher level of protection to the unreliable SI bits can be exploited. Experimental results show that the proposed scheme can reduce the WZ bit-rate up to 13% relative to the state-of-the-art DISCOVER architecture when considering interpolation techniques and by up to 0.9 dB for extrapolation techniques.

Perspective transform motion modeling for improved side information creation

The distributed video coding (DVC) paradigm is based on two well-known information theory results: the Slepian-Wolf and Wyner-Ziv theorems. In a DVC codec, the video signal correlation is mostly exploited at the decoder, providing a flexible distribution of the computational complexity between the encoder and the decoder and error robustness to channel errors. To exploit the temporal correlation, an estimate of the original frame to code, well-known as side information, is typically created at the decoder. One popular approach to side information creation is to perform frame interpolation using a translational motion model derived from already decoded frames. However, this translational model fails to estimate complex camera motions, such as zooms and rotations, and is not accurate enough to estimate the true trajectories of scene objects. In this paper, a new side information creation framework integrating perspective transform motion modeling is proposed. This solution is able to better locally track the trajectories and deformations of each object and increase the accuracy of the overall side information estimation process. Experimental results show peak signal-to-noise ratio gains of up to 1 dB in side information quality and up to 0.5 dB in rate-distortion performance for some video sequences regarding state-of-the-art alternative solutions.

Spatial correlation-based side information refinement for distributed video coding

Distributed video coding (DVC) architecture designs, based on distributed source coding principles, have benefitted from significant progresses lately, notably in terms of achievable rate-distortion performances. However, a significant performance gap still remains when compared to prediction-based video coding schemes such as H.264/AVC. This is mainly due to the non-ideal exploitation of the video sequence temporal correlation properties during the generation of side information (SI). In fact, the decoder side motion estimation provides only an approximation of the true motion. In this paper, a progressive DVC architecture is proposed, which exploits the spatial correlation of the video frames to improve the motion-compensated temporal interpolation (MCTI). Specifically, Wyner-Ziv (WZ) frames are divided into several spatially correlated groups that are then sent progressively to the receiver. SI refinement (SIR) is performed as long as these groups are being decoded, thus providing more accurate SI for the next groups. It is shown that the proposed progressive SIR method leads to significant improvements over the Discover DVC codec as well as other SIR schemes recently introduced in the literature.

화면 간 차이 신호에 대한 화소 영역 위너-지브 비디오 코덱의 비트 에러 내성 성능 평가

DVC(분산 비디오 부호화) 기술은 새로운 패러다임의 기술로서 Slepian-Wolf와 Wyner-Ziv 이론에 기초하고 있다. DVC 기술은 부호화기와 복호화기 사이의 복잡도를 융통성 있게 분할할 수 있게 할 뿐만 아니라, 본질적으로 정보원-채널 통합 부호화를 지원함으로 인해 채널 에러에 대한 강인함을 제공한다. 기존의 많은 연구들은 주로 부호화기의 경량화와 부호화기의 비트율-왜곡 성능 개선에 초점을 맞추어 왔다. 그러나 본 논문에서는 전송 중에 비트 에러가 발생되는 환경에 적합한 DVC 코덱 구조를 제안한다. 제안된 코덱은 데드존이 없는 양자화기와 영을 중심으로 대칭적인 그레이 코드를 사용한다. 모의실험을 통해 제안된 구조에 대해 채널의 연집 비트 에러의 수뿐만 아니라 비트 발생 위치에 따른 성능을 분석한다. 또한, 주어진 응용에 대해 실제 발생되는 채널의 비트 에러에 따라 최대 및 최소 전송율의 크기가 선형적으로 결정될 수 있음을 보인다. DVC(Distributed Video Coding) technique is a new paradigm, which is based on the Slepian-Wolf and Wyner-Ziv theorems. DVC offers not only flexible partitioning of the complexity between the encoder and decoder, but also robustness to channel errors due to intrinsic joint source-channel coding. Many conventional research works have been focused on the light video encoder and its rate-distortion performance improvement. However, in this paper, we propose a new DVC codec which is effectively applicable for error-prone environment. The proposed method adopts a quantiser without dead-zone and symmetric Gray code around zero value. Through computer simulations, the proposed method is evaluated by the bit errors position as well as the number of burst bit errors. Additionally, it is shown that the maximum and minimum transmission rate for the given application can be linearly determined by the number of bit errors.

Efficient Low-Delay Distributed Video Coding

Distributed video coding (DVC) is a video coding paradigm that allows for a low-complexity encoding process by exploiting the temporal redundancies in a video sequence at the decoder side. State-of-the-art DVC systems exhibit a structural coding delay since exploiting the temporal redundancies through motion-compensated interpolation requires the frames to be decoded out of order. To alleviate this problem, we propose a system based on motion-compensated extrapolation that allows for efficient low-delay video coding with low complexity at the encoder. The proposed extrapolation technique first estimates the motion field between the two most recently decoded frames using the Lucas-Kanade algorithm. The obtained motion field is then extrapolated to the current frame using an extrapolation grid. The proposed techniques are implemented into a novel architecture featuring hybrid block-frequency Wyner-Ziv coding as well as mode decision. Results show that having references from both temporal directions in interpolation provides superior rate-distortion performance over a single temporal direction in extrapolation, as expected. However, the proposed extrapolation method is particularly suitable for low-delay coding as it performs better than H.264/AVC intra, and it is even able to outperform the interpolation-based DVC codec from DISCOVER for several sequences.

Perceptual-based distributed video coding

In this paper, we propose a perceptual-based distributed video coding (DVC) technique. Unlike traditional video codecs, DVC applies video prediction process at the decoder side using previously received frames. The predicted video frames (i.e., side information) contain prediction errors. The encoder then transmits error-correcting parity bits to the decoder to reconstruct the video frames from side information. However, channel codes based on i.i.d. noise models are not always efficient in correcting video prediction errors. In addition, some of the prediction errors do not cause perceptible visual distortions. From perceptual coding point of view, there is no need to correct such errors. This paper proposes a scheme for the decoder to perform perceptual quality analysis on the predicted side information. The decoder only requests parity bits to correct visually sensitive errors. More importantly, with the proposed technique, key frames can be encoded at higher rates while still maintaining consistent visual quality across the video sequence. As a result, even the objective PSNR measure of the decoded video sequence will increase too. Experimental results show that the proposed technique improves the R-D performance of a transform domain DVC codec both subjectively and objectively. Comparisons with a well-known DVC codec show that the proposed perceptual-based DVC coding scheme is very promising for distributed video coding framework.

Low delay distributed video coding with refined side information

Distributed video coding (DVC) is a new video coding paradigm based upon two fundamental theoretical results: the Slepian–Wolf and Wyner–Ziv theorems. Among other benefits, this new coding paradigm may allow a flexible complexity allocation between the encoder and the decoder. Several DVC codecs have been developed over the years addressing the specific requirements of emerging applications such as wireless video surveillance and sensor networks. While state-of-the-art DVC codecs, such as the DISCOVER DVC codec, have shown promising RD performance, most DVC codecs in the literature do not consider low delay requirements which are relevant for some of the addressed applications. In this context, the main objective and novelty of this paper is to propose an efficient, low delay and fully practical DVC codec based on the Stanford DVC architecture adopting a side information iterative refinement approach. The obtained performance results show that the developed DVC solution fulfils the objectives regarding relevant benchmarks, notably due to the novel side information creation and correlation noise modeling tools integrated in a side information iterative refinement framework.

Adaptive reconstruction scheme using neighbour pixels in PDWZ coding

Distributed video coding (DVC) is an emerging video coding technology that utilises information theory for distributed sources to build a very simple encoder. In the DVC codec, the reconstruction function for the Wyner-Ziv (WZ) frame is one of the most important modules for improving the quality of the decoded image. An efficient reconstruction algorithm is proposed that uses neighbour pixel information. Simulation results show that the proposed algorithm improves the quality of the decoded image without an increase in the bit rate.

An Improved Decoding Algorithm for DVC Over Multipath Error Prone Wireless Channels

This letter presents an improved decoding algorithm for distributed video coding (DVC) for enhanced performance over error prone wireless channels with multipath fading. The effects of the channel errors on both Wyner-Ziv and key frame bit streams are considered and novel noise models are proposed together with the associated modifications to the decoding algorithm. Simulations are performed using a W-CDMA wireless channel and the results are analyzed to determine the effect of each individual modification. State-of-the-art H.264/AVC is also considered under similar conditions for the comparison. The simulation results show that the proposed modifications provide a significant improvement in the DVC codec performance under unfavorable channel conditions.

Overlapped Block Motion Estimation and Probabilistic Compensation with Application in Distributed Video Coding

It has been recently demonstrated that, in distributed video coding (DVC) side-information dependent modeling of the correlation channel brings significant performance gains over side-information independent assumptions. In this letter, we present a novel technique enabling advanced side-information dependent estimation of the correlation channel at the decoder starting from a very coarse knowledge of it. The proposed technique triggers the design of a spatial-domain DVC codec which enables the suppression of the feedback channel. Experimental results show that the proposed codec achieves similar performance compared to the state-of-the-art in transform-domain Wyner-Ziv video coding while still operating at a fraction of its encoding complexity.

Research of the Virtual Dependency Channel in Distributed Video Coding

The inherent non-stationary characteristic of video signal,such as occlusion phenomena,leads to a complicated motion-compensated prediction technology. In distributed video coding (DVC) because the decoder cannot have access to the current frame,modeling the temporal correlation noise becomes a difficult task. In order to reduce the performance degradation owing to the non-stationary characteristic of video signal,this paper focuses on the research of virtual dependency channel model. Based on a common DVC codec,this paper presents a generalized model of the virtual dependency channel,analysis of which shows that in transformation domain the different subbands have various degree of sensitivity to the temporal correlation noise. According to the analysis this paper proposes a novel VCMDWT model,in which the virtual dependency channel is modeled at the LL subband with property of being more stationary,at the same time the non-stationary high frequency subbans are encoded by SPIHT with intra mode. The simulation results show that the proposed model is especially adaptable to the frames with many occlusion areas,which would be unfit for the pixel domain DVC,and finally improves the rate distortion performance with a gain up to 2.6dBs.