An Improved Error Concealment Technique Based on Multi-View Video Coding

2014 ◽  
Vol 599-601 ◽  
pp. 1383-1386
Author(s):  
Hai Bo Liu ◽  
Xiao Sheng Huang
Keyword(s):  
Image Reconstruction ◽  
Video Coding ◽  
Spatial Correlation ◽  
Error Concealment ◽  
Motion Vector ◽  
Temporal Correlation ◽  
Experimental Results ◽  
Matching Algorithm ◽  
Video Images ◽  
Disparity Vector

In this paper, we propose a improved error concealment technique based on multi-view video coding to recover damaged video images. At first,It uses BMA(Boundary Matching Algorithm) method to recover the lost or erroneously received motion vector or disparity vector,then combining inter-view correlation, temporal correlation and spatial correlation to recover the lost blocks. The JM12.0 model of H.264 standard is used to evaluate the algorithm. And the experimental results show that our algorithm achieved a better image reconstruction.

scholarly journals A New Error Concealment Algorithm Based on Directional Texture Synthesis

2012 ◽  
Vol 6-7 ◽  
pp. 309-314
Author(s):  
Jiang Xin Zhang ◽  
Jin Xie
Keyword(s):  
Image Reconstruction ◽  
Confidence Level ◽  
Error Concealment ◽  
Texture Synthesis ◽  
Experimental Results ◽  
Interpolation Algorithm ◽  
Structure Information ◽  
Video Images ◽  
Directional Texture

In this paper, we propose a novel directional texture synthesis based error concealment algorithm to recover damaged video images. It uses the confidence level and structure information to calculate the priority of patch, which contributes to improve the ability to select the best matching block when the damaged area is very large. The JM86 model of H.264 standard is used to evaluate the algorithm. And experimental results show that our algorithm achieved a better image reconstruction results than the improved Multi-directional texture interpolation algorithm, with 1.2 to 1.4dB gain in PSNR and 0.5 percent to 1 percent gain in SSIM.

Adaptive Error Concealment Technology Based on H.264 for Digital Satellite Set-Top Boxes

2013 ◽  
Vol 273 ◽  
pp. 784-789
Author(s):  
Xiao Juan Tao ◽  
Ling Wang
Keyword(s):  
Packet Loss ◽  
Error Concealment ◽  
Experimental Results ◽  
Spatial Smoothing ◽  
Visual Effect ◽  
Matching Algorithm ◽  
Video Images ◽  
Temporal Domain ◽  
Macro Block ◽  
Multi Mode

In order to improve the decoding performance of digital satellite set-top boxes, this paper proposed a directional boundary matching algorithm on temporal domain for H.264, it considers using the spatial smoothing of video images and the movement consistency in neighbor macro-blocks to restore the damaged macro-block, with pixels matching in three directions on the boundary. On this basis, a adaptive error concealment algorithm of multi-mode is proposed, which avoids the judgment of the partition mode of damaged macro-block. Experimental results show that when in the same case of packet loss, compared with the traditional concealment algorithms, the algorithm proposed in this paper has better performance in the improvement of PSNR and visual effect.

An Efficient Multi-Hypothesis Temporal Error Concealment Method for H.264

2013 ◽  
Vol 433-435 ◽  
pp. 326-329
Author(s):  
Xue Feng Zhan
Keyword(s):  
Standard Deviation ◽  
Error Concealment ◽  
Motion Vector ◽  
Experimental Results ◽  
Fixed Weight ◽  
Temporal Error Concealment ◽  
Weighted Combination

An efficient multi-hypothesis Temporal Error Concealment (TEC) method is proposed in this paper. Two compensated MarcoBlocks (MB) are obtained by two basic TEC approaches. Process of noise Motion Vector (MV) removal is introduced to get compensated MB more accurately. The lost MB is then concealed by weighted combination of the two MBs in which the weight is adjusted adaptively by calculating standard deviation of candidate MV set. Experimental results demonstrate that the proposed method can overcome shortcoming of fixed weight and provide better performance.

Spatial correlation-based approach to motion vector estimation in video coding

1995 ◽  
Author(s):  
Junavit Chalidabhongse ◽  
Sungook Kim ◽  
C.-C. Jay Kuo
Keyword(s):  
Video Coding ◽  
Spatial Correlation ◽  
Motion Vector ◽  
Vector Estimation

scholarly journals Spatial Correlation-Based Motion-Vector Prediction for Video-Coding Efficiency Improvement

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 129 ◽  
Author(s):  
Xiantao Jiang ◽  
Tian Song ◽  
Takafumi Katayama ◽  
Jenq-Shiou Leu
Keyword(s):  
Video Coding ◽  
Spatial Correlation ◽  
Video Quality ◽  
Motion Vector ◽  
Prediction Algorithm ◽  
Computation Complexity ◽  
Coding Efficiency ◽  
Depth Prediction ◽  
Motion Vector Prediction ◽  
Coding Unit

H.265/HEVC achieves an average bitrate reduction of 50% for fixed video quality compared with the H.264/AVC standard, while computation complexity is significantly increased. The purpose of this work is to improve coding efficiency for the next-generation video-coding standards. Therefore, by developing a novel spatial neighborhood subset, efficient spatial correlation-based motion vector prediction (MVP) with the coding-unit (CU) depth-prediction algorithm is proposed to improve coding efficiency. Firstly, by exploiting the reliability of neighboring candidate motion vectors (MVs), the spatial-candidate MVs are used to determine the optimized MVP for motion-data coding. Secondly, the spatial correlation-based coding-unit depth-prediction is presented to achieve a better trade-off between coding efficiency and computation complexity for interprediction. This approach can satisfy an extreme requirement of high coding efficiency with not-high requirements for real-time processing. The simulation results demonstrate that overall bitrates can be reduced, on average, by 5.35%, up to 9.89% compared with H.265/HEVC reference software in terms of the Bjontegaard Metric.

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