Abstract
Motion estimation is a temporal image compression technique, where an nxn block of pixels in the current frame of a video sequence is represented by a motion vector with respect to the best matched block in a search area of the previous frame. In this paper, a low complexity technique for motion estimation is proposed. The proposed technique, first, reduces the n-bit grayscale frames into 1-bit binary frames using morphological filters, and determines the displacement of the edge features of the adjacent frames. While reduction in bit depth requires a small percentage of computation using the full pixel resolution, the search procedure is performed by simple XOR logic operations and 1-b distortion accumulations on the entire search area. Compared to other low complexity techniques, the proposed technique yields better frame reconstruction, operates using simpler arithmetic/logic operations, and possesses a higher degree of parallelism when implemented on a two-dimensional single-instruction stream, multiple-data stream architecture.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 110-116 |
| Number of pages | 7 |
| Journal | Journal of Electronic Imaging |
| Volume | 9 |
| Issue number | 2 |
| State | Published - Apr 2000 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics
- Computer Vision and Pattern Recognition
Cite this
Low complexity block motion estimation using morphological-based feature extraction and XOR operations. / Le, Thinh M.; Mason, R.; Panchanathan, Sethuraman.
In: Journal of Electronic Imaging, Vol. 9, No. 2, 04.2000, p. 110-116.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Low complexity block motion estimation using morphological-based feature extraction and XOR operations
AU - Le, Thinh M.
AU - Mason, R.
AU - Panchanathan, Sethuraman
PY - 2000/4
Y1 - 2000/4
N2 - Motion estimation is a temporal image compression technique, where an nxn block of pixels in the current frame of a video sequence is represented by a motion vector with respect to the best matched block in a search area of the previous frame. In this paper, a low complexity technique for motion estimation is proposed. The proposed technique, first, reduces the n-bit grayscale frames into 1-bit binary frames using morphological filters, and determines the displacement of the edge features of the adjacent frames. While reduction in bit depth requires a small percentage of computation using the full pixel resolution, the search procedure is performed by simple XOR logic operations and 1-b distortion accumulations on the entire search area. Compared to other low complexity techniques, the proposed technique yields better frame reconstruction, operates using simpler arithmetic/logic operations, and possesses a higher degree of parallelism when implemented on a two-dimensional single-instruction stream, multiple-data stream architecture.
AB - Motion estimation is a temporal image compression technique, where an nxn block of pixels in the current frame of a video sequence is represented by a motion vector with respect to the best matched block in a search area of the previous frame. In this paper, a low complexity technique for motion estimation is proposed. The proposed technique, first, reduces the n-bit grayscale frames into 1-bit binary frames using morphological filters, and determines the displacement of the edge features of the adjacent frames. While reduction in bit depth requires a small percentage of computation using the full pixel resolution, the search procedure is performed by simple XOR logic operations and 1-b distortion accumulations on the entire search area. Compared to other low complexity techniques, the proposed technique yields better frame reconstruction, operates using simpler arithmetic/logic operations, and possesses a higher degree of parallelism when implemented on a two-dimensional single-instruction stream, multiple-data stream architecture.
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M3 - Article
VL - 9
SP - 110
EP - 116
JO - Journal of Electronic Imaging
JF - Journal of Electronic Imaging
SN - 1017-9909
IS - 2
ER -