Yunsong Wu

Linear predicted hexagonal search algorithm with moments

A novel Linear Hashtable Method Predicted Hexagonal Search (LHMPHS) method for block based motion compensation is proposed. Fast block matching algorithms use the origin as the initial search center, which often does not track motion very well. To improve the accuracy of the fast BMAs, we employ a predicted starting search point, which reflects the motion trend of the current block. The predicted search centre is found closer to the global minimum. Thus the center-biased BMAs can be used to find the motion vector more efficiently. The performance of the algorithm is evaluated by using standard video sequences, considers the three important metrics: The results show that the proposed algorithm enhances the accuracy of current hexagonal algorithms and is better than Full Search, Logarithmic Search etc.

Two-pass hexagonal algorithm with improved hashtable structure for motion estimation

This paper presents an improved two-pass hexagonal (TPA) algorithm constituted by linear hashtable motion estimation algorithm (LHMEA) and hexagonal search (HEXBS) for motion estimation. In the TPA, motion vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of macroblocks (MBs). The hashtable structure of LHMEA is improved compared to the original TPA and LHMEA. The evaluation of the algorithm considers the three important metrics being processing time, compression rate and PSNR. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms.

Parallel Linear Hashtable Motion Estimation Algorithm for Parallel Video Processing

This paper presents a parallel linear hashtable motion estimation algorithm (LHMEA). Most parallel video compression algorithms focus on group of picture (GOP). Based on LHMEA we proposed earlier, we developed a parallel motion estimation algorithm focus inside of frame. We divide each reference frames into equally sized regions. These regions are going to be processed in parallel to increase the encoding speed significantly. The theory and practice speed up of parallel LHMEA according to the number of PCs in the cluster are compared and discussed. Motion vectors (MV) are generated from the first-pass LHMEA and used as predictors for second-pass hexagonal search (HEXBS) motion estimation, which only searches a small number of macroblocks (MBs). We evaluated distributed parallel implementation of LHMEA of TPA for real time video compression

Linear hashtable method predicted hexagonal search algorithm with spatial related criterion

The paper presents a novel Linear Hashtable Method Predicted Hexagonal Search (LHMPHS) method for block base motion compensation. It bases on the edge motion estimation algorithm called hexagonal search (HEXBS). Most current variances of hexagonal search are investigated. On the basis of research of previous algorithms, we proposed a Linear Hashtable Motion Estimation Algorithm (LHMEA). The proposed algorithm introduces hashtable into motion estimation. It uses information from the current frame. The criterion uses spatially correlated macroblock (MB)s information. Except for coarse search, the spatially correlated information is also used in inner search. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms such as Full Search, Logarithmic Search etc. The evaluation considers the three important metrics: time, compression rate and PSNR.

Linear hashtable motion estimation algorithm for distributed video processing

This paper presents a parallel Linear Hashtable Motion Estimation Algorithm (LHMEA). Most parallel video compression algorithms focus on Group of Picture (GOP). Based on LHMEA we proposed earlier [1][2], we developed a parallel motion estimation algorithm focus inside of frame. We divide each reference frames into equally sized regions. These regions are going to be processed in parallel to increase the encoding speed significantly. The theory and practice speed up of parallel LHMEA according to the number of PCs in the cluster are compared and discussed. Motion Vectors (MV) are generated from the first-pass LHMEA and used as predictors for second-pass Hexagonal Search (HEXBS) motion estimation, which only searches a small number of Macroblocks (MBs). We evaluated distributed parallel implementation of LHMEA of TPA for real time video compression.

Improved two-pass hexagonal algorithm with parallel implementation for video coding

This paper presents a paralleled two-pass hexagonal (TPA) algorithm constituted by linear hashtable motion estimation algorithm (LHMEA) and hexagonal search (HEXBS) for motion estimation. In the TPA, motion vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of macroblocks (MBs). We introduced hashtable into video processing and completed parallel implementation. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. It discusses how parallel video coding on load balanced multiprocessor systems can help, especially on motion estimation. The effect of load balancing for improved performance is discussed. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms

Parallel Linear Hashtable Motion Estimation Algorithm

This paper presents a parallel linear hashtable motion estimation algorithm (LHMEA). Most parallel video compression algorithms focus on group of picture (GOP). Based on LHMEA we proposed earl[1][2], we developed a parallel motion estimation algorithm focus inside of frame. We divide each reference frames into equally sized regions. These regions are going to be processed in parallel to increase the encoding speed significantly. The theory and practice speed up of parallel LHMEA according to the number of PCs in the cluster are compared and discussed. Motion vectors (MV) are generated from the first-pass LHMEA and used as predictors for second-pass hexagonal search (HEXBS) motion estimation, which only searches a small number of Macroblocks (MBs). We evaluated distributed parallel implementation of LHMEA of TPA for real time video compression.

Linear predicted two-pass hexagonal algorithm with parallel implementation for motion estimation

This paper presents a paralleled two-pass hexagonal (TPA) algorithm constituted by linear hashtable motion estimation algorithm (LHMEA) and hexagonal search (HEXBS) for motion estimation. In the TPA, motion vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of macroblocks (MBs). We introduced hashtable into video processing and completed parallel implementation. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. It discusses how parallel video coding on load balanced multiprocessor systems can help, especially on motion estimation. The effect of load balancing for improved performance is discussed. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms

Paralleled two-pass hexagonal algorithm for motion estimation

This paper presents a paralleled two-pass hexagonal (TPA) algorithm constituted by linear hashtable motion estimation algorithm (LHMEA) and hexagonal search (HEXBS) for motion estimation. In the TPA, motion vectors (MV) are generated from the first-pass LHMEA and are used as predictors for second-pass HEXBS motion estimation, which only searches a small number of macroblocks (MBs). We introduced hashtable into video processing and completed parallel implementation. We propose and evaluate parallel implementations of the LHMEA of TPA on clusters of workstations for real time video compression. It discusses how parallel video coding on load balanced multiprocessor systems can help, especially on motion estimation. The effect of load balancing for improved performance is discussed. The performance of the algorithm is evaluated by using standard video sequences and the results are compared to current algorithms

Two-Pass Hexagonal Algorithm with Parallel Implementation for Video Coding

Thispaperpresents a paralleled Two-Pass Hexagonal (TPA)algorithm constituted byLinear Hashtable MotionEstimation Algorithm (LHMEA)andHexagonal Search (HEXBS)formotion estimation. IntheTPA,Motion Vectors (MV)aregenerated fromthefirst-pass LHMEA and areusedaspredictors forsecond-pass HEXBS motion estimation, whichonlysearches a smallnumberof Macroblocks (MBs).We introduced hashtable intovideo processing and completed parallel implementation. We propose andevaluate parallel implementations oftheLHMEA ofTPA on clusters ofworkstations forrealtimevideo compression. Itdiscusses howparallel videocoding onload balanced multiprocessor systems canhelp,especially on motion estimation. Theeffect ofloadbalancing forimproved performance isdiscussed. Theperformance ofthealgorithm is evaluated byusing standard video sequences andtheresults arecompared tocurrent algorithms.