scholarly journals A Novel Consistent Quality Driven for JEM Based Distributed Video Coding

Algorithms ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 130 ◽  
Author(s):  
Dinh Trieu Duong ◽  
Huy Phi Cong ◽  
Xiem Hoang Van

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.

Author(s):  
Huynh Van Luong ◽  
Søren Forchhammer ◽  
Jürgen Slowack ◽  
Jan De Cock ◽  
Rik Van de Walle

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.


Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1427
Author(s):  
Wei Wang ◽  
Jianhua Chen

In order to effectively improve the quality of side information in distributed video coding, we propose a side information generation scheme based on a coefficient matrix improvement model. The discrete cosine transform coefficient bands of the Wyner–Ziv frame at the encoder side are divided into entropy coding coefficient bands and distributed video coding coefficient bands, and then the coefficients of entropy coding coefficient bands are sampled, which are divided into sampled coefficients and unsampled coefficients. For sampled coefficients, an adaptive arithmetic encoder is used for lossless compression. For unsampled coefficients and the coefficients of distributed video coding coefficient bands, the low density parity check accumulate encoder is used to calculate the parity bits, which are stored in the buffer and transmitted in small amount upon decoder request. At the decoder side, the optical flow method is used to generate the initial side information, and the initial side information is improved according to the sampled coefficients by using the coefficient matrix improvement model. The experimental results demonstrate that the proposed side information generation scheme based on the coefficient matrix improvement model can effectively improve the quality of side information, and the quality of the generated side information is improved by about 0.2–0.4 dB, thereby improving the overall performance of the distributed video coding system.


2017 ◽  
Vol 11 (2) ◽  
pp. 126-134 ◽  
Author(s):  
Pudi Raj Bhagath ◽  
Kallol Mallick ◽  
Jayanta Mukherjee ◽  
Sudipta Mukopadhayay

2011 ◽  
Vol 58-60 ◽  
pp. 2079-2084
Author(s):  
An Hong Wang ◽  
Yi Zheng ◽  
Zhi Hong Li ◽  
Yu Yang Wang

Nowadays, the rate-distortion performance of distributed video coding (DVC) is not satisfied despite its distinct contribution to low-complexity encoding. This paper presents a new residual DVC using an optimized trellis coded quantization (TCQ) to improve the performance of the current schemes. H.264/AVC intra-frame coding is firstly used to obtain the referenced frame, and then the residual between Wyner-Ziv frame and the referenced frame is Wyner-Ziv encoded with a proposed optimized TCQ which consists of the improved quadtree and the improved TCQ, both considering the characters of wavelet coefficients in different sub-bands. Experimental results show that the proposed scheme outperforms the referenced in rate-distortion performance, and the goal of low-complexity encoding is achieved.


Author(s):  
Farah Diyana Abdul Rahman ◽  
Dimitris Agrafiotis ◽  
Ahmad Imran Ibrahim

In multimedia transmission, it is important to rely on an objective quality metric which accurately represents the subjective quality of processed images and video sequences. Reduced-reference metrics make use of side-information that is transmitted to the receiver for estimating the quality of the received sequence with low complexity. In this paper, an Edge-based Dissimilarity Reduced-Reference video quality metric with low overhead bitrate is proposed. The metric is evaluated by finding the dissimilarity between the edge information of original and distorted sequences. The edge degradation can be detected in this manner as perceived video quality is highly associated with edge structural. Due to the high overhead using the Soergel distance, it is pertinent to find a way to reduce the overhead while maintaining the edge information that can convey the quality measure of the sequences. The effects of different edge detection operator, video resolution and file compressor are investigated. The aim of this paper is to significantly reduce the bitrate required in order to transmit the side information overhead as the reduced reference video quality metric. From the results obtained, the side information extracted using Sobel edge detector maintained consistency throughout the reduction of spatial and temporal down-sample.


Author(s):  
Jelena Vlaović ◽  
Drago Žagar ◽  
Snježana Rimac-Drlje ◽  
Mario Vranješ

With the development of Video on Demand applications due to the availability of high-speed internet access, adaptive streaming algorithms have been developing and improving. The focus is on improving user’s Quality of Experience (QoE) and taking it into account as one of the parameters for the adaptation algorithm. Users often experience changing network conditions, so the goal is to ensure stable video playback with satisfying QoE level. Although subjective Video Quality Assessment (VQA) methods provide more accurate results regarding user’s QoE, objective VQA methods cost less and are less time-consuming. In this article, nine different objective VQA methods are compared on a large set of video sequences with various spatial and temporal activities. VQA methods used in this analysis are: Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), MultiScale Structural Similarity Index (MS-SSIM), Video Quality Metric (VQM), Mean Sum of Differences (DELTA), Mean Sum of Absolute Differences (MSAD), Mean Squared Error (MSE), Netflix Video Multimethod Assessment Fusion (Netflix VMAF) and Visual Signal-to-Noise Ratio (VSNR). The video sequences used for testing purposes were encoded according to H.264/AVC with twelve different target coding bitrates, at three different spatial resolutions (resulting in a total of 190 sequences). In addition to objective quality assessment, subjective quality assessment was performed for these sequences. All results acquired by objective VQA methods have been compared with subjective Mean Opinion Score (MOS) results using Pearson Linear Correlation Coefficient (PLCC). Measurement results obtained on a large set of video sequences with different spatial resolutions show that VQA methods like SSIM and VQM correlate better with MOS results compared to PSNR, SSIM, VSNR, DELTA, MSE, VMAF and MSAD. However, the PLCC results for SSIM and VQM are too low (0.7799 and 0.7734, respectively), for the usage of these methods in streaming services instead of subjective testing. These results suggest that more efficient VQA methods should be developed to be used in streaming testing procedures as well as to support the video segmentation process. Furthermore, when comparing results obtained for different spatial resolutions, it can be concluded that the quality of video sequences encoded at lower spatial resolutions in cases of lower target coding bitrate is higher compared to the quality of video sequences encoded at higher spatial resolutions at the same target coding bitrate, particularly when video sequences with higher spatial and temporal information are used.


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