An Improved Error Concealment Based on Redundant Motion Vector Information

2012 ◽  
Vol 532-533 ◽  
pp. 1219-1224
Author(s):  
Hong Tao Deng
Keyword(s):  
Video Transmission ◽  
Error Concealment ◽  
Video Quality ◽  
Motion Vector ◽  
Compressed Video ◽  
Vector Information ◽  
Vector Estimation ◽  
Channel Errors ◽  
Bit Stream

During video transmission over error prone network, compressed video bit-stream is sensitive to channel errors that may degrade the decoded pictures severely. In order to solve this problem, error concealment technique is a useful post-processing tool for recovering the lost information. In these methods, how to estimate the lost motion vector correctly is important for the quality of decoded picture. In order to recover the lost motion vector, an Decoder Motion Vector Estimation (DMVE) criterion was proposed and have well effect for recover the lost blocks. In this paper, we propose an improved error concealment method based on DMVE, which exploits the accurate motion vector by using redundant motion vector information. The experimental results with an H.264 codec show that our method improves both subjective and objective decoder reconstructed video quality, especially for sequences of drastic motion.

An Efficient Motion Vector Recovery and Reconstruction Method for Spatiotemporal Video Error Concealment

2019 ◽  
Vol 9 (4) ◽  
pp. 28-48
Author(s):  
Ansari Vaqar Ahmed ◽  
Uday Pandit Khot
Keyword(s):  
Mahalanobis Distance ◽  
Error Concealment ◽  
Motion Vector ◽  
Reconstruction Method ◽  
Recovery Method ◽  
Video Error Concealment ◽  
Distance Approach ◽  
Measurement Approach ◽  
Measure Technique ◽  
Total Average

In this article, an efficient spatiotemporal video error concealment (EC) based on motion vector (MV) recovery and a pixel reconstruction (PR) method is proposed. The pixel-based motion vector with partition (PMVP) is modified by using Mahalanobis distance (MD) rather than Euclidean distance (ED) for recovering MVs, as MD uses standard deviation and covariance of available pixels. Further, the MD gives more accuracy for non-square cluster compared to ED. This modified pixel-based motion vector with partition (MPMVP) algorithm is further upgrade by two different strategies. First, by using voting priority of available MVs based on the probabilities of similar directions. Second, by considering separate horizontal and vertical directions of available MVs in voting priority. For pixel reconstruction, modified spiral pixel reconstruction (MSPR) algorithm based on directional edge recovery method using minimum and maximum Mahalanobis distance from available pixels of surrounding MBs is proposed. Mahalanobis distance approach is most optimized similarity measure technique compared to other distance measurement approach to obtained lost motion vectors. These proposed EC techniques are compared with existing EC techniques like, SPR EC using ED, PMVP based EC with ED, and MV Interpolation by Zhou's method for various packet loss rates (PLRs) as 3%, 7%, 16%, 20% and quantization parameters (QPs) as 20, 24, 28, 32, 36. For total average in PLR of 3%, 7%, 16% and 20%, MSPR is having better PSNR compared to PMVP by 2.516, 2.29, 2.06 and 2.02 dB, respectively; and compared to SPR by 0.796, 0.718, 0.643 and 0.631 dB, respectively.

Motion Consistence and Textural Coherence based Error Concealment Algorithm for Corrupted Macroblock

2011 ◽  
Vol 383-390 ◽  
pp. 1605-1610
Author(s):  
Jing Chen ◽  
Can Hui Cai
Keyword(s):  
Reference Frame ◽  
Video Transmission ◽  
Error Concealment ◽  
State Of The Art ◽  
Motion Vector ◽  
Visual Quality ◽  
The State ◽  
Boundary Matching ◽  
Video Error Concealment

In this paper, an error concealment algorithm for lost macroblock (MB), named motion consistence and textural coherence based error concealment algorithm (MCTC), is proposed to meet the requirement of video transmission over error-prone channels. A directional predicted motion vector (MV) set is setup by using the motion consistence between MV co-located in reference frame and the neighboring MVs of the lost MB. To find out an optimal MV from this candidate MV set, a textural coherence based boundary matching (TCBM) criterion is proposed. The experiment results show that the MCTC outperforms the state-of-the-art video error concealment methods in both objective and subjective visual quality.

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