1 April 2008 Interlaced-to-progressive conversion using adaptive projection-based global and representative local motion estimation
Young Duk Kim, Joonyoung Chang, Gun Shik Shin, Moon Gi Kang
Author Affiliations +
Abstract
We propose a motion-compensation-based deinterlacing algorithm using global and representative local motion estimation. The proposed algorithm first divides an entire image into five regions of interest (ROIs) according to the temporally predicted motion type (i.e., global or local) and the spatial position. One of them is for global motion estimation and the others are for local motion estimation. Then, dominant motions of respective ROIs are found by adaptive projection approach. The adaptive projection method not only estimates dominant local motions with low computational cost, but also ensures consistent global motion estimation. Using the estimated motion vectors, adaptive two-field bidirectional motion compensation is performed. The arbitration rules, measuring the reliability of motion compensation accurately, produce high-quality deinterlaced frames by effectively combining the results of motion compensation and the stable intrafield deinterlacing. Experimental results show that the proposed deinterlacing algorithm provides better image quality than the existing algorithms in both subjective and objective measures.
©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)
Young Duk Kim, Joonyoung Chang, Gun Shik Shin, and Moon Gi Kang "Interlaced-to-progressive conversion using adaptive projection-based global and representative local motion estimation," Journal of Electronic Imaging 17(2), 023008 (1 April 2008). https://doi.org/10.1117/1.2938998
Published: 1 April 2008
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CITATIONS
Cited by 4 scholarly publications and 3 patents.
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KEYWORDS
Motion estimation

Reliability

Multiplexing

Global Positioning System

Motion measurement

Image quality

Video

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