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兵工学报 ›› 2011, Vol. 32 ›› Issue (11): 1331-1336.

• 论文 • 上一篇    下一篇

动态射线数字图像序列降噪算法及快速实现

杨民1, 孟凡勇2, 梁丽红3, 魏东波1   

  1. (1.北京航空航天大学 机械工程及自动化学院, 北京 100191;2.中国科学院过程工程研究所 多相复杂系统国家重点实验室, 北京 100190;3.中国特种设备检测研究院, 北京 100013)
  • 收稿日期:2010-03-12 修回日期:2010-03-12 上线日期:2014-05-04
  • 通讯作者: 杨民 E-mail:minyang.ndt@263.net
  • 作者简介:杨民(1975—),男,副教授,博士
  • 基金资助:
    国家自然科学基金资助项目(6087208061077011); 中国科学院过程工程研究所多相复杂系统国家重点实验室开放基金资助项目(MPCS- 2011-D-03)

Denoising Algorithm for Dynamic Digital X-ray Image Sequences and Its Fast Implementation

YANG Min1, MENG Fan-yong2, LIANG Li-hong3, WEI Dong-bo1   

  1. (1.School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;2.State Key Laboratory of Multiphase Complex Systems,Institute of Process Engineering, Chinese Academy of Science,3.China Special Equipment Inspection and Research Institute,Beijing 100013, China)
  • Received:2010-03-12 Revised:2010-03-12 Online:2014-05-04
  • Contact: YANG Min E-mail:minyang.ndt@263.net

摘要: 为了实现动态射线数字成像(DR)系统的快速降噪,分析了X射线数字实时成像系统的噪声特点和原始的基于图像序列的NL-means降噪算法的不足,提出了一种改进的NL-means序列图像降噪算法。同时,为了解决NL-means降噪算法计算量大、运算速度慢的问题,利用可编程图形处理单元(GPU) 并行计算和高速浮点计算特性,将图像映射为GPU中的纹理,采用多线程并行计算,使得NL-means算法在GPU中加速执行。实验结果表明,改进之后的算法有效地抑制了动态DR图像中的随机噪声,同时保留了图像的细节信息。GPU加速方法可以在不损失图像信息的前提下,实现实时降噪。

关键词: 信息处理技术, 射线数字成像, 图像降噪, NL-means算法, 图形处理单元

Abstract: In order to realize the fast noise reduction in the dynamic digital radiography (DR) imaging system, the system’s noise characteristics and the disadvantages of the original NL-means denoising algorithm were studied. An improved NL-means noise reduction algorithm was proposed. Meanwhile, in order to solve its calculation complexity problem, graphic processing unit (GPU) was applied to make use of its high parallel and fast floating-point calculation abilities. In the implementation, the image was mapped to the GPU’s texture and multi-thread parallel calculation was adopted. The experimental results showed that the improved NL-means noise reduction algorithm could effectively restrain the quantum noise and improve the resolution of DR image sequences. In addition, the acceleration with GPU could realize the real-time denoising without the loss of image information.

Key words: information processing, digital radiography, image denoising, NL-means algorithm, graphic processing unit

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