TY - JOUR
T1 - The gray prediction search algorithm for block motion estimation
AU - Jou, Jer Min
AU - Chen, Pei Yin
AU - Sun, Jian Ming
N1 - Funding Information:
Manuscript received January 26, 1998; revised January 18, 1999. This work was supported in part by the National Science Council, R.O.C., under Grant NSC-87-2213-E-006-031. This paper was recommended by Associate Editor B. Zeng. The authors are with the Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan 70101 R.O.C. Publisher Item Identifier S 1051-8215(99)07024-X.
PY - 1999/9
Y1 - 1999/9
N2 - Due to the temporal and spatial correlation of the image sequence, the motion vector of a block is highly related to the motion vectors of its adjacent blocks in the same image frame. If we can obtain useful and enough information from the adjacent motion vectors, the total number of search points used to find the motion vector of the block may be reduced significantly. Using that idea, an efficient gray prediction search (GPS) algorithm for block motion estimation is proposed in this paper. Based on the gray system theory, the GPS can determine the motion vectors of image blocks quickly and correctly. The experimental results show that the proposed algorithm performs better than other search algorithms, such as 3SS, CS, PHODS, 4SS, BBGDS, SES, and PSA, in terms of six different measures: 1) average mean square error per pixel; 2) average peak signal-to-noise ratio; 3) average prediction errors per pixel; 4) average entropy of prediction errors; 5) average percentage of unpredictable pels per frame; and 6) average search points per block.
AB - Due to the temporal and spatial correlation of the image sequence, the motion vector of a block is highly related to the motion vectors of its adjacent blocks in the same image frame. If we can obtain useful and enough information from the adjacent motion vectors, the total number of search points used to find the motion vector of the block may be reduced significantly. Using that idea, an efficient gray prediction search (GPS) algorithm for block motion estimation is proposed in this paper. Based on the gray system theory, the GPS can determine the motion vectors of image blocks quickly and correctly. The experimental results show that the proposed algorithm performs better than other search algorithms, such as 3SS, CS, PHODS, 4SS, BBGDS, SES, and PSA, in terms of six different measures: 1) average mean square error per pixel; 2) average peak signal-to-noise ratio; 3) average prediction errors per pixel; 4) average entropy of prediction errors; 5) average percentage of unpredictable pels per frame; and 6) average search points per block.
UR - http://www.scopus.com/inward/record.url?scp=0032660644&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0032660644&partnerID=8YFLogxK
U2 - 10.1109/76.785721
DO - 10.1109/76.785721
M3 - Article
AN - SCOPUS:0032660644
SN - 1051-8215
VL - 9
SP - 843
EP - 848
JO - IEEE Transactions on Circuits and Systems for Video Technology
JF - IEEE Transactions on Circuits and Systems for Video Technology
IS - 6
ER -