| Paper: | IMDSP-P12.6 | ||
| Session: | Image Coding | ||
| Time: | Friday, May 21, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Image and Video Coding | ||
| Title: | A MEMORY-EFFICIENT FAST ENCODING METHOD FOR VECTOR QUANTIZATION USING 2-PIXEL-MERGING SUM PYRAMID | ||
| Authors: | Zhibin Pan; Tohoku University | ||
| Koji Kotani; Tohoku University | |||
| Tadahiro Ohmi; Tohoku University | |||
| Abstract: | Vector quantization (VQ) is a famous signal compression method. In a framework of VQ encoding, the fast search method for finding the best-matched codeword (winner) is a key issue because it is the time bottleneck for practical applications. To speed up VQ encoding process, some fast search methods that are based on the concept of multi-resolutions by introducing a pyramid data structure have already been proposed in previous works [5]-[7]. However, there still exist two serious problems in them. First, they need a lot of extra memories for storing all purposely- constructed intermediate levels in a pyramid, which becomes an overhead of memory. Second, they completely discard the obtained Euclidean distance that has already been computed at an intermediate level whenever a rejection test fails at this level during a search process, which becomes an overhead of computation.In order to solve the overhead problems of both memory and computation as described above, this paper proposes a memory-efficient storing way for a vector and a recursive computation way for Euclidean distance level by level based on a 2-pixel-merging (2-PM) sum pyramid, which can thoroughly reuse the obtained value of Euclidean distance at any level to compute the next rejection test condition at a successive level. Mathematically, this method does not need any extra memories at all and can reduce the original computational burden that is needed in a conventional non-recursive computation way to about half at each level. Experimental results confirmed that the proposed method outperforms the previous works obviously. | ||
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