基于二维特征向量的快速分形编码方法  

Fast method for fractal coding based on two-dimensional characteristic vector

作　　者：刘明[1] 叶正麟[1] 陈作平[1] 

机构地区：[1]西北工业大学理学院,西安710072

出　　处：《计算机工程与应用》2007年第8期82-84,共3页Computer Engineering and Applications

基　　金：国家自然科学基金(the National Natural Science Foundation of China under Grant No.10071060);西北工业大学研究生创业种子基金项目(No.200656)

摘　　要：编码时间过长是目前分形图像压缩存在的主要问题,对图像块进行分类是解决这一问题的一类重要方法,然而在诸多分类方法中,编码时间的减少通常是以牺牲图像解码质量为代价的。为此,提出了一种基于二维特征向量的自适应分类方法。并把图像的1、2阶矩不变量作为图像的主副特征得到了一种能够较好地保证图像解码质量的快速分形编码方法。Long coding time is the main problem in fraetal image compression in present,to which classification of image blocks is an important and efficient solution.However,among most classification methods,the decreasing of time usually cause quality sacrifice.Therefore we propose a method called＂Adaptive Classification based on Two-dimensional Characteristic Vector＂.Using first order and second order quadrature of image as main and secondary feature to obtain a fast method for fractal coding which can get better quality of decoded image.

关 键 词：分形图像压缩 矩 特征向量 自适应分类 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]