首页 > 论文 > 激光与光电子学进展 > 55卷 > 9期(pp:90901--1)

分割太赫兹全息再现像的复合方法的比较

Comparison of Composite Image Segmentation Methods for Terahertz Holography Reconstruction Images

  • 摘要
  • 论文信息
  • 参考文献
  • 被引情况
  • PDF全文
分享:

摘要

为实现太赫兹同轴全息再现图像识别, 通常需要图像分割以提取图像特征。太赫兹同轴数字全息再现图像包含一定程度的噪声, 影响分割质量。本文针对太赫兹同轴全息再现像特点采用了基于裁剪、镜像扩展、滤波和直方图多项式拟合的复合分割方法, 用该方法分别对垫片和齿轮的2.52 THz同轴全息真实再现像进行了处理, 并分步与基本全局阈值法和大津法进行了比较分析, 同时用马修斯相关系数进行了客观评价。实验结果表明, 该复合方法可以得到较好的分割结果。

Abstract

Image segmentation is usually needed to extract the features in order to recognize images of terahertz inline digital holography reconstruction. The images of terahertz inline digital holography reconstruction contain various degree of noise, which affects the quality of segmentation. In this paper, the composite segmentation method based on the clipping, mirror expansion, filtering and histogram polynomial fitting is adopted for the characteristics of terahertz holographic reconstructed image. By using this method, the 2.52 THz images of terahertz inline digital holography reconstruction of gasket and gear are processed and compared step by step with the basic global threshold method and the Otsu method, and objectively evaluated with Mathews correlation coefficient. Experimental results show that the composite method can get better segmentation results.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TN249

DOI:10.3788/lop55.090901

所属栏目:全息

基金项目:国家自然科学基金(61377110)

收稿日期:2018-03-15

修改稿日期:2018-04-13

网络出版日期:2018-04-24

作者单位    点击查看

巩文盼:哈尔滨工业大学可调谐激光技术国家级重点实验室, 黑龙江 哈尔滨 150080
李琦:哈尔滨工业大学可调谐激光技术国家级重点实验室, 黑龙江 哈尔滨 150080
董儒汲:哈尔滨工业大学可调谐激光技术国家级重点实验室, 黑龙江 哈尔滨 150080

联系人作者:巩文盼(hitgongwenpan@163.com)

【1】Wang Z W, Li Q, Yuan J. Image quality evaluation and analysis of zero-order diffraction elimination method in terahertz off-axis digital holography[J]. Laser & Optoelectronics Progress, 2017, 54(11): 111102.
汪泽文, 李琦, 袁静. 太赫兹离轴数字全息消零级方法的像质评价及其分析[J]. 激光与光电子学进展, 2017, 54(11): 111102.

【2】Zhao F Z, Liang H Y, Wu X L, et al. Active contour segmentation model based on local and global Gaussian fitting[J]. Laser & Optoelectronics Progress, 2017, 54(5): 051006.
赵方珍, 梁海英, 巫湘林, 等. 基于局部和全局高斯拟合的主动轮廓分割模型[J]. 激光与光电子学进展, 2017, 54(5): 051006.

【3】Zhu Z L, Wang J F. Image segmentation based on adaptive fuzzy C-means and post processing correction[J]. Laser & Optoelectronics Progress, 2018, 55(1): 011004.
朱占龙, 王军芬. 基于自适应模糊C均值与后处理的图像分割算法[J]. 激光与光电子学进展, 2018, 55(1): 011004.

【4】Nie F Y, Li J Q, Zhang P F, et al. A threshold selection method for image segmentation based on Tsallis relative entropy[J]. Laser & Optoelectronics Progress, 2017, 54(7): 071002.
聂方彦, 李建奇, 张平凤, 等. 一种基于Tsallis相对熵的图像分割阈值选取方法[J]. 激光与光电子学进展, 2017, 54(7): 071002.

【5】Gonzalez R C, Woods R E, Eddins S L. Digital image processing using MATLAB[M]. Ruan Q Q, Transl.. 3th ed. Beijing: Publishing House of Electronics Industry, 2006: 305-307.
拉斐尔·冈萨雷斯, 理查德·伍兹, 史蒂文·埃丁斯. 数字图像处理: MATLAB版[M]. 阮秋琦, 译. 3版. 北京: 电子工业出版社, 2006: 305-307.

【6】Ridler T W, Calvard S. Picture thresholding using an iterative selection method[J]. IEEE Transactions on Systems Man & Cybernetics, 1978, 8(8): 630-632.

【7】Magid A, Rotman S R, Weiss A M. Comments on picture thresholding using an iterative selection method[J]. IEEE Transactions on Systems Man & Cybernetic, 1990, 20(5): 1238-1239.

【8】Otsu N. A thresholding selection method from gray-level histogram[J]. IEEE Transactions on Systems Man & Cybernetics, 1979, 9(1): 62-66.

【9】Jiao A S M, Tsang P W M, Poon T C, et al. Automatic decomposition of a complex hologram based on the virtual diffraction plane framework[J]. Journal of Optics, 2014, 16(7): 075401.

【10】Jiao S, Tsang P W M, Poon T C, et al. Enhanced autofocusing in optical scanning holography based on hologram decomposition[J]. IEEE Transactions on Industrial Informatics, 2017, 13(5): 2455-2463.

【11】Zhou M. Low SNR infrared weak target image segmentation algorithm[J]. Laser & Infrared, 2004, 34(3): 225-228.
周铭. 低信噪比红外小目标图像的分割方法[J]. 激光与红外, 2004, 34(3): 225-228.

【12】Wang N, Peng Q Y, Deng B Q. Background segmentation in medical image[J]. Chinese Journal of Medical Imaging Technology, 2010, 26(8): 1573-1575.
王娜, 彭青玉, 邓保青. 医学图像背景分割[J]. 中国医学影像技术, 2010, 26(8): 1573-1575.

【13】Yu C B, Kong Q D, Qian Z W, et al. A dynamic threshold segmentation method based on bidirectional polynomial fitting[J]. Application of Electronic Technique, 2016, 42(3): 110-112, 119.
余成波, 孔庆达, 钱泽文, 等. 基于双向多项式拟合的动态阈值分割算法[J]. 电子技术应用, 2016, 42(3): 110-112, 119.

【14】Zhang X, Zhao Y M, Zhang C L. Passive terahertz image segmentation algorithm[J]. High Power Laser and Particle Beams, 2013, 25(6): 1597-1600.
张馨, 赵源萌, 张存林. 被动式太赫兹图像分割算法[J]. 强激光与粒子束, 2013, 25(6): 1597-1600.

【15】Stephani H, Heise B, Katletz S, et al. A feature set for enhanced automatic segmentation of hyperspectral terahertz images[C]∥2011 Irish Machine Vision and Image Processing Conference, September 7-9, 2011, Dublin, Ireland. New York: IEEE, 2011: 117-122.

【16】Buades A, Coll B, Morel J M. A review of image denoising algorithms, with a new one[J]. Multiscale Modeling & Simulation, 2005, 4(2): 490-530.

引用该论文

Gong Wenpan,Li Qi,Dong Ruji. Comparison of Composite Image Segmentation Methods for Terahertz Holography Reconstruction Images[J]. Laser & Optoelectronics Progress, 2018, 55(9): 090901

巩文盼,李琦,董儒汲. 分割太赫兹全息再现像的复合方法的比较[J]. 激光与光电子学进展, 2018, 55(9): 090901

您的浏览器不支持PDF插件,请使用最新的(Chrome/Fire Fox等)浏览器.或者您还可以点击此处下载该论文PDF