ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2017, Vol. 54 ›› Issue (9): 2077-2091.doi: 10.7544/issn1000-1239.2017.20160520

• 图形图像 • 上一篇    下一篇

基于纹理特征的自适应插值

张云峰1,姚勋祥1,包芳勋2,张彩明3   

  1. 1(山东财经大学计算机科学与技术学院 济南 250014);2(山东大学数学学院 济南 250100);3(山东大学计算机科学与技术学院 济南 250100) (yfzhang@sdufe.edu.cn)
  • 出版日期: 2017-09-01
  • 基金资助: 
    国家自然科学基金项目(61373080,61672018,61402261,61373088,61272431,61332015);山东省高等学校优势学科人才团队培育计划

Adaptive Interpolation Scheme Based on Texture Features

Zhang Yunfeng1, Yao Xunxiang1, Bao Fangxun2, Zhang Caiming3   

  1. 1(School of Computer Science & Technology, Shandong University of Finance and Economics, Jinan 250014);2(School of Mathematics, Shandong University, Jinan 250100);3(School of Computer Science & Technology, Shandong University, Jinan 250100)
  • Online: 2017-09-01

摘要: 在传统有理插值函数的基础上构造出一种新的混合插值模型.该混合插值模型是有理函数与分形插值函数的有机整体,可由形状参数和尺度因子唯一确定.由于分形是刻画图像复杂度的有效工具,引入分形维数描述纹理的复杂程度.首先,提出一种基于局部分形维数的自适应阈值选取的方法,将整幅图像划分为纹理区域和非纹理区域.在纹理区域采用有理分形函数插值,在非纹理区域采用有理函数插值.尤其在有理分形插值模型中,提出一种基于分形维数的精确计算尺度因子的方法.最后,通过优化形状参数进一步提高插值图像质量.实验结果表明:提出的基于图像特征的混合插值模型与当前经典算法相比,尤其是在处理纹理图像方面,具有明显优势.

关键词: 混合插值, 局部分形维数, 自适应阈值, 参数优化, 有理分形

Abstract: A new interpolation model is proposed based on the bivariate rational interpolation. This model contains rational fractal interpolation and bivariate rational interpolation, which is identified uniquely by the values of iterated function system parameters (scaling factor and shape parameters). Due to efficient capacity of fractal in description of complex phenomenon, the fractal dimension is employed to texture analysis. Based on the analysis of local fractal dimension (LFD), a new local adaptive threshold method is proposed. And then images can be divided into texture region and non-texture region. As for texture regions, rational fractal interpolation is used to get high resolution images. Similarly, rational interpolation is used in non-texture region. Considering the parameters in rational fractal interpolation model, we propose a new method for calculating the scaling factor. Further, in order to improve the quality of interpolated image, shape parameters optimization technique is applied. Experimental results show that the presented model achieves very competitive performance with the state-of-the-art interpolation algorithms.

Key words: mixing interpolant, local fractal dimension, adaptive threshold, parameters optimizing, rational fractal

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