标题: | 多阶层使用明可斯基不等式而得的动态估计影像压缩 Motion Estimation by the Hierarchical Use of Minkowski's Inequality |
作者: | 卢静怡 Lu, Jing-Yi 林志青 Ja-Chen Lin 资讯科学与工程研究所 |
关键字: | 动态估计;明可斯基不等式;motion estimation;Minkowski's inequality |
公开日期: | 1995 |
摘要: | 在本论文中,我们根据两种不同的评断标准而提出了两套新的快速整体搜 寻法,以便做动态影像压缩里的动态估计。我们的方法使用了金字塔架构 。由于我们已事先推导出该架构中每一层所得到的误差测量值之间的单调 关系,所以许多不可能进入决赛的候选区块能够被及早丢弃,这使得我们 的方法能大量地降低计算时间。实验结果显示我们的方法所需的计算量确 实远低于1995年刊登在IEEE期刊上的“连续消除法”所需。另一方面,正 如同“连续消除法”一样,我们所提出的方法也可获得和传统“整体搜寻 法”相同的精确度。若与着名的“三步搜寻法”比较,虽然“三步搜寻法 ”通常找到的并不是最佳解,其计算速度并不会比我们这种保证找到最佳 解的方法快很多。 In this thesis, two fast full search (FS) algorithms for motion estimation are presented according to two different matching criteria called Mean Absolute Difference (MAD) and Minimized Maximum Difference (MiniMax), respectively. Based on the monotonic relation between the distortion measures obtained for distinct layers of a pyramid structure, the proposed method successively rejects many impossible candidates considered in the FS and thus reduces the computation time significantly. Experimental results demonstrate that the computation load is much less than a recently introduced method known as the Successive Elimination Algorithm (SEA) of which the estimation accuracy is also the same as that of the FS. The algorithm proposed here has the property that the optimal result can be obtained with the processing speed not too far away from that of the Three-Step Search (TSS) which is one of the widely-used fast algorithms giving non-optimal estimation. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#NT840394013 http://hdl.handle.net/11536/60454 |
显示于类别: | Thesis |