| Paper: | IMDSP-P1.6 | ||
| Session: | Video Coding | ||
| Time: | Tuesday, May 18, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Image and Video Coding | ||
| Title: | A NEW EFFICIENT SIMILARITY METRIC AND GENERIC COMPUTATION STRATEGY FOR PATTERN-BASED VERY LOW BIT-RATE VIDEO CODING | ||
| Authors: | Manoranjan Paul; Monash University | ||
| Manzur Murshed; Monash University | |||
| Laurence Dooley; Monash University | |||
| Abstract: | In the context of very low bit-rate video coding, pattern representations of a moving region (MR) in block-based motion estimation and compensation has become increasingly attractive. Generally, all existing pattern-matching algorithms apply a similarity metric involving elementary operations, to compute the mismatch between a MR and a particular fixed pattern in order to select the best-matching pattern from a fixed-size codebook of predefined patterns. In this paper, an efficient similarity metric together a new generic computation strategy is presented by considering only the mismatch areas of MRs. It is theoretically proven that for a specific MR in a macroblock, the new similarity metric selects exactly the same pattern as existing metrics, while the resulting computational coding efficiency is improved by between 21% and 58% compared with the H.263 low bit-rate coding standard. | ||
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