An Improved Error Concealment Algorithm for Wireless Video Applications

2010 ◽  
Vol 171-172 ◽  
pp. 531-535
Author(s):  
Ji Ping Liu ◽  
Bo Wang
Keyword(s):  
Video Transmission ◽  
Error Concealment ◽  
Median Filter ◽  
Motion Vector ◽  
Wireless Video ◽  
Motion Vectors ◽  
Extrapolation Algorithm ◽  
Block Motion ◽  
Motion Vector Field ◽  
Loss Frame

This paper develops a new error concealment algorithm for the whole-frame losses in wireless video transmission based on H.264/AVC.At first,we propose a forward motion vector extrapolation algorithm based on variable-size block motion vector estimation to obtain the motion vector field of the loss frame without yielding the hole problems. Then, we partition the missing frame into several object regions by clustering the motion vectors, furthermore, we apply median filter to reconstruct the motion vectors for hole areas based on the reliabilities of neighboring motion vectors. Finally, all macroblocks in the lost frame are estimated by using the extrapolated motion vectors. Experimental results show that the proposed algorithm provides better image quality than conventional methods both objectively and subjectively.

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.

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.

DENSE ESTIMATION OF OPTICAL FLOW FIELD WITHIN THE MPEG-2 COMPRESSED DOMAIN

2009 ◽  
Vol 09 (03) ◽  
pp. 435-448
Author(s):  
GAOBO YANG ◽  
WEIWEI CHEN ◽  
XIAO JING WANG ◽  
ZHAOYANG ZHANG
Keyword(s):  
Flow Field ◽  
Optical Flow ◽  
Motion Vector ◽  
Compressed Domain ◽  
Motion Vectors ◽  
Optical Flow Field ◽  
Intensity Information ◽  
Motion Vector Field ◽  
First Motion ◽  
Dct Coefficients

A dense estimation of optical flow field within the MPEG-2 compressed domain is proposed, which utilizes only the compressed-domain information, i.e. motion vectors and DCT coefficients. First, motion vectors are pre-processed to estimate the DCT coefficients for P and B frames. Second, initial optical flow is estimated with Black's optical flow estimation framework, in which DC image is substituted by DC+2AC image to provide more intensity information. Third, high confidence test is exploited to generate the dense and accurate motion vector field by removing false and noisy motion vectors. It preserves the advantages of compressed domain processing and improves the existent MPEG velocity field in terms of accuracy and density. Experimental results demonstrate that the proposed approach can provide a satisfactory motion analysis for compressed-domain video object extraction.

Motion correction in PET/CT

2005 ◽  
Vol 44 (S 01) ◽  
pp. S46-S50 ◽  
Author(s):  
M. Dawood ◽  
N. Lang ◽  
F. Büther ◽  
M. Schäfers ◽  
O. Schober ◽  
...  
Keyword(s):  
Optical Flow ◽  
Motion Correction ◽  
Motion Vector ◽  
Emission Tomography ◽  
Cardiac Pet ◽  
Novel Approach ◽  
Positron Emission ◽  
Pet Ct ◽  
Flow Algorithm ◽  
Motion Vector Field

Summary:Motion in PET/CT leads to artifacts in the reconstructed PET images due to the different acquisition times of positron emission tomography and computed tomography. The effect of motion on cardiac PET/CT images is evaluated in this study and a novel approach for motion correction based on optical flow methods is outlined. The Lukas-Kanade optical flow algorithm is used to calculate the motion vector field on both simulated phantom data as well as measured human PET data. The motion of the myocardium is corrected by non-linear registration techniques and results are compared to uncorrected images.

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