Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVC
Merge mode can achieve a considerable coding gain because of reducing the cost of coding motion information in video codecs. However, the simple adoption of the motion information from the neighbouring blocks may not achieve the optimal performance as the motion correlation between the pixels and th...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Advances in Multimedia |
| Online Access: | http://dx.doi.org/10.1155/2019/8202385 |
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| author | Hongwei Guo Xiangsuo Fan Lei Min |
| author_facet | Hongwei Guo Xiangsuo Fan Lei Min |
| author_sort | Hongwei Guo |
| collection | DOAJ |
| description | Merge mode can achieve a considerable coding gain because of reducing the cost of coding motion information in video codecs. However, the simple adoption of the motion information from the neighbouring blocks may not achieve the optimal performance as the motion correlation between the pixels and the neighbouring block decreases with their distance increasing. To address this problem, the paper proposes a Euclidean distance-based weighted prediction algorithm as an additional candidate in the merge mode. First, several predicted blocks are generated by motion compensation prediction (MCP) with the motion information from available neighbouring blocks. Second, an additional predicted block is generated by a weighted average of the predicted blocks above, where the weighted coefficient is related to Euclidean distances from the neighbouring candidate to the pixel points in the current block. Finally, the best merge mode is selected by the rate distortion optimization (RDO) among the original merge candidates and the additional candidate. Experimental results show that, on the joint exploration test model 7.0 (JEM 7.0), the proposed algorithm achieves better coding performance than the original merge mode under all configurations including random access (RA), low delay B (LDB), and low delay P (LDP), with a slight coding complexity increase. Especially for the LDP configuration, the proposed method achieves 1.50% bitrate saving on average. |
| format | Article |
| id | doaj-art-2cac7a8951c74144bddafb54e001ae8a |
| institution | OA Journals |
| issn | 1687-5680 1687-5699 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Multimedia |
| spelling | doaj-art-2cac7a8951c74144bddafb54e001ae8a2025-08-20T02:24:04ZengWileyAdvances in Multimedia1687-56801687-56992019-01-01201910.1155/2019/82023858202385Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVCHongwei Guo0Xiangsuo Fan1Lei Min2School of Engineering, Honghe University, Mengzi, Yunnan 661100, ChinaSchool of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou, Guangxi 545006, ChinaInstitute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, Sichuan 610209, ChinaMerge mode can achieve a considerable coding gain because of reducing the cost of coding motion information in video codecs. However, the simple adoption of the motion information from the neighbouring blocks may not achieve the optimal performance as the motion correlation between the pixels and the neighbouring block decreases with their distance increasing. To address this problem, the paper proposes a Euclidean distance-based weighted prediction algorithm as an additional candidate in the merge mode. First, several predicted blocks are generated by motion compensation prediction (MCP) with the motion information from available neighbouring blocks. Second, an additional predicted block is generated by a weighted average of the predicted blocks above, where the weighted coefficient is related to Euclidean distances from the neighbouring candidate to the pixel points in the current block. Finally, the best merge mode is selected by the rate distortion optimization (RDO) among the original merge candidates and the additional candidate. Experimental results show that, on the joint exploration test model 7.0 (JEM 7.0), the proposed algorithm achieves better coding performance than the original merge mode under all configurations including random access (RA), low delay B (LDB), and low delay P (LDP), with a slight coding complexity increase. Especially for the LDP configuration, the proposed method achieves 1.50% bitrate saving on average.http://dx.doi.org/10.1155/2019/8202385 |
| spellingShingle | Hongwei Guo Xiangsuo Fan Lei Min Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVC Advances in Multimedia |
| title | Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVC |
| title_full | Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVC |
| title_fullStr | Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVC |
| title_full_unstemmed | Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVC |
| title_short | Euclidean Distance-Based Weighted Prediction for Merge Mode in HEVC |
| title_sort | euclidean distance based weighted prediction for merge mode in hevc |
| url | http://dx.doi.org/10.1155/2019/8202385 |
| work_keys_str_mv | AT hongweiguo euclideandistancebasedweightedpredictionformergemodeinhevc AT xiangsuofan euclideandistancebasedweightedpredictionformergemodeinhevc AT leimin euclideandistancebasedweightedpredictionformergemodeinhevc |