半叉迹特征的快速分形图像编码  

Semi-cross trace feature fast fractal image coding

作　　者：袁宗文[1] 鲁业频[1] 杨汉生[1] 

机构地区：[1]巢湖学院电子工程与电气自动化学院

出　　处：《计算机工程与应用》2016年第3期197-201,共5页Computer Engineering and Applications

基　　金：安徽省高等学校自然科学研究项目基金(No.KJ2011B103)

摘　　要：传统的分形图像编码时间过长,限制了它的应用。为了加快编码速度,提出基于半叉迹特征的快速分形编码算法,该算法主要包括:定义子块半叉迹特征,导出子块的均方根误差与子块半叉迹特征之间的关系。实验结果表明:该算法较基本分析编码算法,在解码图像PSNR平均提高约0.63 d B的情况下,平均加快编码速度55倍;较文献[10]提出的主对角和算法和文献[11]提出的叉迹算法,在编码时间不变的情况下,改善了编码性能,提高了解码图像质量;基于子块特征的快速编码算法,其编码性能与图像的复杂程度有关,细节信息越丰富的图像,编码性能越差。Traditional fractal image coding is very time consuming, so its application is limited. To speed up the encoding speed, this paper proposes fast fractal coding algorithm based on semi-cross trace feature. The algorithm includes： defining semi-cross trace feature, achieving the relationship between the root mean square of sub-blocks error and the semi-cross trace feature of sub-blocks. Experimental results show that： when decoded image PSNR increases of about average 0.63 dB, the encoding speeds up average 55 times; the algorithm improves coding performance and improves the quality of decoded image in case of unchanged encoding time, compared with main diagonal sum feature from the literature[10] and cross trace feature from the literature[11]; the fast encoding algorithm based on sub-block feature, the coding performance is related to the complexity of image. The more abundance image details, the worse coding performance.

关 键 词：分形 分形图像编码 编码性能 子块特征 半叉迹 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]