计算机工程与应用 ›› 2016, Vol. 52 ›› Issue (3): 197-201.

• 图形图像处理 • 上一篇    下一篇

半叉迹特征的快速分形图像编码

袁宗文,鲁业频,杨汉生   

  1. 巢湖学院 电子工程与电气自动化学院,安徽 巢湖 238000
  • 出版日期:2016-02-01 发布日期:2016-02-03

Semi-cross trace feature fast fractal image coding

YUAN Zongwen, LU Yepin, YANG Hansheng   

  1. College of Electronic Engineering & Electrical Automation, Chaohu University, Chaohu, Anhui 238000, China
  • Online:2016-02-01 Published:2016-02-03

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 dB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。

关键词: 分形, 分形图像编码, 编码性能, 子块特征, 半叉迹

Abstract: 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.

Key words: fractal, fractal image coding, coding performance, sub-block feature, semi-cross trace