This paper presents a new strategy of particle-pair(PP) for vector quantization(VQ) in image coding.
本文给出了一种新的图像矢量量化码书的优化设计方法——粒子对算法。
Nowadays, wavelet transform, vector quantization and embedded encoding has been the primary technique and study focus for image compression, to which people attach their more importance.
目前，小波变换、矢量量化以及嵌入式编码已经成为图像压缩的主要技术及研究热点，越来越受到重视。
The principle of fuzzy vector quantization (FVQ) for image coding is discussed in this paper, and an exponential fuzzy learning vector quantization algorithm (EFLVQ) is proposed.
本文分析了模糊矢量量化(FVQ)图像编码的原理，提出了一种指数型模糊学习矢量量化算法(EFLVQ)。
The paper introduces deburr algorithm before line trace in the course of vector quantization of binary map image, and it can receive better effect through applying for the algorithm.
介绍对二值地图图像矢量化过程中的线跟踪操作之前的去毛刺算法，应用此算法可以得到更好的线跟踪效果。
The paper introduces deburr algorithm before line trace in the course of vector quantization of binary map image, and it can receive better effect through applying for the algorithm.
介绍对二值地图图像矢量化过程中的线跟踪操作之前的去毛刺算法，应用此算法可以得到更好的线跟踪效果。
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