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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| Format: | Article |
| Language: | zho |
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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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| _version_ | 1841539852608208896 |
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| author | Chuan-ming SONG Yan-wen GUO Xiang-hai WANG Dan LIU |
| author_facet | Chuan-ming SONG Yan-wen GUO Xiang-hai WANG Dan LIU |
| author_sort | Chuan-ming SONG |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-f371094e9c6d43a4b8f0736775c59b32 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2013-07-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-f371094e9c6d43a4b8f0736775c59b322025-01-14T06:40:49ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2013-07-0134597059673470Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantizationChuan-ming SONGYan-wen GUOXiang-hai WANGDan LIUA 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.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.07.007/video codingmotion estimationblock matchingfuzzy quantizationlow bit-resolution |
| spellingShingle | Chuan-ming SONG Yan-wen GUO Xiang-hai WANG Dan LIU Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization Tongxin xuebao video coding motion estimation block matching fuzzy quantization low bit-resolution |
| title | Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization |
| title_full | Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization |
| title_fullStr | Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization |
| title_full_unstemmed | Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization |
| title_short | Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization |
| title_sort | motion estimation algorithm using 2 bit depth pixel and fuzzy quantization |
| topic | video coding motion estimation block matching fuzzy quantization low bit-resolution |
| url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2013.07.007/ |
| work_keys_str_mv | AT chuanmingsong motionestimationalgorithmusing2bitdepthpixelandfuzzyquantization AT yanwenguo motionestimationalgorithmusing2bitdepthpixelandfuzzyquantization AT xianghaiwang motionestimationalgorithmusing2bitdepthpixelandfuzzyquantization AT danliu motionestimationalgorithmusing2bitdepthpixelandfuzzyquantization |