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Joint Framework for Motion Validity and Estimation Using Block Overlap

delete2013-04-01
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PRE
AI
S
Santoro, Michael *
G
Ghassan AlRegib
Y
Y. Altunbasak
DOI:10.1109/TIP.2012.2235452delete
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Abstract

Abstract

En 中文
This paper presents a block-overlap-based validity metric for use as a measure of motion vector (MV) validity and to improve the quality of the motion field. In contrast to other validity metrics in the literature, the proposed metric is not sensitive to image features and does not require the use of neighboring MVs or manual thresholds. Using a hybrid de-interlacer, it is shown that the proposed metric outperforms other block-based validity metrics in the literature. To help regularize the ill-posed nature of motion estimation, the proposed validity metric is also used as a regularizer in an energy minimization framework to determine the optimal MV. Experimental results show that the proposed energy minimization framework outperforms several existing motion estimation methods in the literature in terms of MV and interpolation quality. For interpolation quality, our algorithm outperforms all other block-based methods as well as several complex optical flow methods. In addition, it is one of the fastest implementations at the time of this writing.
Keywords:
Block matching
de-interlacing
motion vector (MV)
reliability
true motion estimation
validity
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Journal

IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
IF:
13.7
Papers:
1.0W
Citations:
8.4W

Organization

G
Georgia Institute of Technology
Scholars:
1.8W
Papers: 1.4W
Citations: 5.9W
U
university system of georgia
Scholars:
7.3W
Papers: 6.5W
Citations: 101