系统工程与电子技术

• 软件、算法与仿真 • 上一篇    下一篇

基于成像机理分析的图像混叠去除

张晔, 魏然   

  1. 哈尔滨工业大学电子与信息工程学院, 黑龙江 哈尔滨 150001
  • 出版日期:2015-02-10 发布日期:2010-01-03

Image aliasingremoving based on imaging-mechanism analysis

ZHANG Ye,WEI Ran   

  1. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
  • Online:2015-02-10 Published:2010-01-03

摘要:

去混叠技术是图像处理领域重要的方法之一。目前的去混叠算法多数都是在空间域进行的,因此它们都忽略了这样一个事实,即图像的频域成分混合是产生混叠的根本原因,而其在空间域所造成的视觉失真,仅是一种表现。基于此,提出了一种基于成像机理分析的去混叠算法,改变了现有算法仅从空间域角度解决混叠的现状。该方法在从成像机理角度分析混叠产生原因的基础上,利用分形技术对图像所丢失的高频信息进行了补偿,从而实现混叠去除。实验结果表明,算法不仅能够在空间域上消除混叠给视觉带来的影响,而且能够在频域上,更多的恢复高频成分的信息。

Abstract:

Aliasing-removing technique is one of the most important methods in the field of image processing. Almost every existing aliasing-removing algorithm is spatial-domain based, neglecting the fact that aliasing is naturally frequency-component mixing at frequency domain, and the undesirable visual effect of aliasing is just a phenomenon in spatial-domain. Inspired by such fact, in this paper, a novel imaging imaging-mechanism analysis based aliasingremoving algorithm is proposed, breaking through the limitation of existing methods that reduce aliasing in spatial domain. Based on the analysis of the cause for aliasing in view of sensor imaging process, fractal technique is introduced so as to compensate for the missing high-frequency component, and thus accomplish aliasing-removing. The experiment results show that the proposed method can not only remove visual artifacts in spatial domain, brought by aliasing, but also recover more high-frequency component information in frequency domain.