CAJ | 학술논문

矢量量化是一种有效的数据压缩技术，由于其算法简单，具有较高的压缩率，因而被广泛应用于数据压缩编码领域。通过对图像块灰度特征的研究，根据图像的平滑与否，提出了对图像进行均值和矢量量化复合编码算法，该算法对平滑图像块采用均值编码，对非平滑块采用矢量量化编码。这不仅节省了平滑码字的存储空间，提高了码书存储效率，并且编码速度大大提高。同时采用码字旋转反色（2R）压缩算法将码书的存储容量减少到1/8，并结合最近邻块扩展搜索算法（EBNNS）对搜索算法进行优化。在保证图像画质的前提下，整个系统的图像编码速度比全搜索的普通矢量量化平均提高约7.7倍。
시량양화시일충유효적수거압축기술，유우기산법간단，구유교고적압축솔，인이피엄범응용우수거압축편마영역。통과대도상괴회도특정적연구，근거도상적평활여부，제출료대도상진행균치화시량양화복합편마산법，해산법대평활도상괴채용균치편마，대비평활괴채용시량양화편마。저불부절성료평활마자적존저공간，제고료마서존저효솔，병차편마속도대대제고。동시채용마자선전반색（2R）압축산법장마서적존저용량감소도1/8，병결합최근린괴확전수색산법（EBNNS）대수색산법진행우화。재보증도상화질적전제하，정개계통적도상편마속도비전수색적보통시량양화평균제고약7.7배。
As an effective technology for data compression, Vector Quantization(VQ)is widely used in the field of data coding because of its simple algorithm and high compression rate. According to analyzing the character of image block, a hybrid algo-rithm combining mean-value and VQ is presented in this paper, which encodes smooth image block and nonsmooth block by mean-value and VQ algorithm respectively. The presented algorithm can save the storage space by removing the smooth code-words in the codebook and speed up encoding process. In order to improve the storage efficiency, the algorithm which can com-press original codebook to 1/8 by rotating and reversing codewords is adopted. At the same time, the search algorithm is opti-mized using Extend Block Nearest Neighbor(EBNNS)method. The whole system encoding speed can achieve about 7.7 times faster than full search VQ algorithm.