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Low Precision Global Motion Estimation for Video Compression- A Generalized Framework

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5 Author(s)
Yang, K. ; Sch. of Inf. Technol. & Electr. Eng., Univ. of New South Wales at Australian Defence Force Acad., Canberra, ACT ; Frater, M.R. ; Huntington, E.H. ; Pickering, M.R.
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Global motion estimation (GME) is a fundamental problem in video compression and has been one of the most complex algorithms in digital video processing. The efficiency of real-time video processing operations has an important impact on the cost and realizability of complex algorithms, such as global motion estimation. Most digital video processing is carried out with a precision of 8 bits per pixel, however there has always been interest in low-complexity algorithms. One way of achieving low-complexity is through low precision, such as might be achieved by quantization of each pixel to a single bit. Previous approaches to one-bit motion estimation have achieved quantization through a combination of spatial filtering/averaging and threshold setting. In this paper we present a generalized framework for precision reduction in video compression. Motivated by this generalized framework, we show that bit-plane selection provides higher performance, with lower complexity, than conventional approaches to quantization.

Published in:

Digital Image Computing: Techniques and Applications (DICTA), 2008

Date of Conference:

1-3 Dec. 2008