Multi-Hypothesis Temporal Error Concealment Scheme Based on Kalman Filter

2013 ◽  
Vol 373-375 ◽  
pp. 574-578
Author(s):  
Xue Feng Zhan
Keyword(s):  
Kalman Filter ◽  
Error Concealment ◽  
Experimental Results ◽  
Motion Vectors ◽  
Previous Frame ◽  
Temporal Error Concealment

In this paper, we present a multi-hypothesis scheme of Temporal Error Concealment (TEC). The lost block is concealed by several hypothesis blocks in the previous frame, and the corresponding Motion Vectors (MVs) of hypothesis blocks are derived using a kalman filter based on the similarity of local MVs. The processing is at the level of 8x8 block and the tendency in horizontal and vertical orientations is considered to predict the candidate MVs. Experimental results demonstrate that the proposed method can provide better performance as compared with the conventional approaches.

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.

Real-Time Identification and Tracking of Infrared Markers Based on Kalman Filter

2012 ◽  
Vol 249-250 ◽  
pp. 1147-1153
Author(s):  
Qiao Na Xing ◽  
Da Yuan Yan ◽  
Xiao Ming Hu ◽  
Jun Qin Lin ◽  
Bo Yang
Keyword(s):  
Kalman Filter ◽  
Visible Light ◽  
Real Time ◽  
Complex Terrain ◽  
Experimental Results ◽  
Identification Method ◽  
In The Wild ◽  
Real Time Identification

Automatic equipmenttransportation in the wild complex terrain circumstances is very important in rescue or military. In this paper, an accompanying system based on the identification and tracking of infrared LEDmarkers is proposed. This system avoidsthe defect that visible-light identification method has. In addition, this paper presents a Kalman filter to predict where infraredmarkers may appear in the nextframe imageto reduce the searchingarea of infrared markers, which remarkablyimproves the identificationspeed of infrared markers. The experimental results show that the algorithm proposed in this paper is effective and feasible.

Influence analysis of measurement errors in satellite attitude determination based on extended Kalman filter

2012 ◽  
Vol 116 (1178) ◽  
pp. 373-389
Author(s):  
Y. Jiao ◽  
J. Wang ◽  
X. Pan ◽  
H. Zhou
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Measurement Errors ◽  
Attitude Determination ◽  
Previous Analysis ◽  
Measurement Model ◽  
Experimental Results ◽  
Influence Analysis ◽  
Satellite Attitude ◽  
Structural Error

Abstract The satellite attitude determination approach based on the Extended Kalman Filter (EKF) has been widely used in many real applications. However, the accuracy of this method largely depends on the fitness of measurement model. We aim to analyse the influence of measurement errors to the accuracy of EKF based attitude determination approach in this paper. The measurement errors, which are divided into structural error and nonstructural error by their influences, are analysed in principle. In the setting of the combination of star sensors and gyros, according to the property of innovation, we employ the technique of correlation test to analyse the influences of different kinds of measurement errors. Experimental results demonstrate the effectiveness of our previous analysis.

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.

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