Lai Jim Z C, Liaw Yi-Ching
Department of Information Engineering and Computer Science, Feng-Chia University, Taichung, Taiwan 407, ROC.
IEEE Trans Image Process. 2004 Dec;13(12):1554-8. doi: 10.1109/tip.2004.837559.
In this paper, a new and fast-searching algorithm for vector quantization is presented. Two inequalities, one used for terminating the searching process and the other used to delete impossible codewords, are presented to reduce the distortion computations. Our algorithm makes use of a vector's features (mean value, edge strength, and texture strength) to reject many unlikely codewords that cannot be rejected by other available approaches. Experimental results show that our algorithm is superior to other algorithms in terms of computing time and the number of distortion calculations. Compared with available approaches, our method can reduce the computing time and the number of distortion computations significantly. Compared with the best method of reducing distortion computation, our algorithm can further reduce the number of distortion calculations by 29% to 58.4%. Compared with the best encoding algorithm for vector quantization, our approach also further reduces the computing time by 8% to 47.7%.
本文提出了一种新的快速矢量量化搜索算法。给出了两个不等式，一个用于终止搜索过程，另一个用于删除不可能的码字，以减少失真计算。我们的算法利用矢量的特征（均值、边缘强度和纹理强度）来排除许多其他现有方法无法排除的不太可能的码字。实验结果表明，我们的算法在计算时间和失真计算次数方面优于其他算法。与现有方法相比，我们的方法可以显著减少计算时间和失真计算次数。与减少失真计算的最佳方法相比，我们的算法可以进一步将失真计算次数减少29%至58.4%。与最佳矢量量化编码算法相比，我们的方法还可以进一步将计算时间减少8%至47.7%。
