摘要
提出利用四叉树自适应图像划分、源块池柔性分类并结合人类视觉特性的高速分形图像编码算法.与其它同类算法相比,该算法在编码速度、压缩比和图像质量等方面均有显著提高.
Traditionally, fractal image compression suffers from lengthy encoding time in measure of hours. In this paper, combined with characteristics of human visual system, a flexible classification technique is proposed. This yields a corresponding adaptive algorithm which can cut down the encoding time into second′s magnitude. Experiment results suggest that the algorithm can balance the overall encoding performance efficiently, that is, with a higher speed and a better PSNR gain.
出处
《武汉大学学报(自然科学版)》
CSCD
1998年第3期292-296,共5页
Journal of Wuhan University(Natural Science Edition)
基金
国家"863"高科技和测绘遥感信息工程国家重点实验室资
关键词
图像编码
分形图像编码
迭代函数系统
image coding, fractal image coding, iterated function system(IFS), partitioned iterated function system(PIFS), characteristics of human visual system