Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization
A motion estimation algorithm was proposed using 2 bit-depth pixels. The reduction of pixel depth was first formalized by two successive steps, namely interval partitioning and interva mapping. The former is a many-to-one mapping which determines motion estimation performance, while the latter is a...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2013-07-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.07.007/ |
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| Summary: | A motion estimation algorithm was proposed using 2 bit-depth pixels. The reduction of pixel depth was first formalized by two successive steps, namely interval partitioning and interva mapping. The former is a many-to-one mapping which determines motion estimation performance, while the latter is a one-to-one mapping. A non-uniform quantization method was then presented to compute three initial thresholds of the interval partitioning. These initial thre-sholds were subsequently refined by using a membership function to solve the mismatch of pixel values near them caused by signal noise and so on. Afterwards, a matching criterion was discussed suitable for the motion estimation using 2 bit-depth pixels. A novel motion estimation algorithm was consequently addressed based on 2 bit-depth pixels and fuzzy quantiza-tion. To further predict the precision of the proposed algorithm, a bit resolution reduction error-motion vector precision model was built by exploiting the auto-correlation function. Extensive experimental results show that the proposed algo-rithm can always achieve high motion estimation precis rious characteristics, especially for those with detailed scene and complex motion. Compared with traditional 2 bit motion estimation, the proposed algorithm gains 0.27 dB improvement in terms of average peak signal-to-noise ratio of motion compensation. |
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| ISSN: | 1000-436X |