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结合多尺度分解和梯度绝对值算子的显微图像清晰度评价方法
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  • 英文篇名:Micro-image definition evaluation using multi-scale decomposition and gradient absolute value
  • 作者:崔光茫 ; 张克奇 ; 毛磊 ; 徐之海 ; 冯华君
  • 英文作者:Cui Guangmang;Zhang Keqi;Mao Lei;Xu Zhihai;Feng Huajun;Ningbo Yongxin Optics Co., Ltd.;State Key Lab of Modern Optical Instrumentation, Zhejiang University;School of Electronics and Information, Hangzhou Dianzi University;
  • 关键词:显微图像 ; 清晰度评价 ; 非下采样剪切波变换 ; 梯度绝对值算子
  • 英文关键词:micro-images;;image definition evaluation;;non-subsampled Shearlet transform(NSST);;gradient absolute value
  • 中文刊名:GDGC
  • 英文刊名:Opto-Electronic Engineering
  • 机构:宁波永新光学股份有限公司;浙江大学现代光学仪器国家重点实验室;杭州电子科技大学电子信息学院;
  • 出版日期:2019-06-15
  • 出版单位:光电工程
  • 年:2019
  • 期:v.46;No.355
  • 基金:国家自然科学基金资助项目(61805063);; 浙江省博士后科研择优资助项目~~
  • 语种:中文;
  • 页:GDGC201906007
  • 页数:11
  • CN:06
  • ISSN:51-1346/O4
  • 分类号:59-69
摘要
针对显微图像自动对焦和成像系统质量评价问题,结合多尺度分解工具和梯度绝对值算子设计,提出了一种显微图像清晰度评价算法。采用非下采样剪切波分解,对输入的显微图像进行多尺度、多方向变换,得到一幅低频子带图像和若干幅高频子带图像。结合抗噪阈值设置,计算各子带图像的梯度绝对值算子和,利用图像清晰度变化对于低频和高频子带系数影响的差异,将高低频梯度绝对值算子的比值作为最终的显微图像清晰度评价数值。开展了仿真论证实验和实拍论证实验,实验结果表明,所提出的清晰度评价算法具有较好的单调性和抗噪特性,和几种经典的评价算法相比,本文方法得到的评价结果在灵敏度、稳定性和鲁棒性方面表现更为优异,具有很好的实际应用价值。
        Aimed at the problem of automatic focus and image system quality evaluation in microscopy imaging, a micro-image definition evaluation method is presented by combining multi-scale decomposition tools and absolute gradient operators. The multiscale and multidirectional non-subsampled Shearlet transform is utilized to decompose the input micro image into a low frequency sub-band image and a number of high frequency sub-band images.Combined with the anti-noise threshold setting, the gradient absolute sum values of each sub-band image were calculated. By using the different effects of image sharpness on the low-frequency and high-frequency sub-band coefficients, the ratio of the high-frequency to low-frequency gradient absolute value operator was taken as the final evaluation value of the microscopic image sharpness. The simulation experiment and actual experiments were carried out and the experimental results illustrated that the proposed approach has good monotonicity and anti-noise characteristics. Compared with other classic evaluation algorithms, the presented method obtained superior performance on sensitivity, stability and robustness. It has very good practical application values.
引文
[1]Ilhan H A,Dogar M,Ozcan M.Digital holographic microscopy and focusing methods based on image sharpness[J].Journal of Microscopy,2014,255(3):138-149.
    [2]Rudnaya M E,Mattheij R M M,Maubach J M L.Evaluating sharpness functions for automated scanning electron microscopy[J].Journal of Microscopy,2010,240(1):38-49.
    [3]Zheng X,Ai L F,Liu K,et al.Auto-focusing function for microscopic images based on global and local gray-scale variation[J].Laser&Optoelectronics Progress,2017,54(8):081801.郑馨,艾列富,刘奎,等.结合全局和局部灰度变化的显微图像自动聚焦函数[J].激光与光电子学进展,2017,54(8):081801.
    [4]Zhao J F,Mao L,Liu C,et al.Microscopy imaging definition criterion using visual attention mechanism and edge spreading evaluation[J].Acta Photonica Sinica,2015,44(7):0711002.赵巨峰,毛磊,刘承,等.视觉注意机制与边缘展宽衡量相结合的显微成像清晰度评价[J].光子学报,2015,44(7):0711002.
    [5]Zhou H K,Ge P S,Feng H L.Micro-image definition evaluation algorithm based on non-subsampled Contourlet transform[J].Journal of Hefei University of Technology(Natural Science),2014,37(10):1204-1209.周厚奎,葛品森,冯海林.基于非下采样Contourlet变换的显微图像清晰度评价算法[J].合肥工业大学学报(自然科学版),2014,37(10):1204-1209.
    [6]Jiang M S,Zhang N N,Zhang X D,et al.Applications of hybrid search strategy in microscope autofocus[J].Opto-Electronic Engineering,2017,44(7):685-694.江旻珊,张楠楠,张学典,等.混合搜索法在显微镜自动对焦中的应用[J].光电工程,2017,44(7):685-694.
    [7]Huang D T.Study on auto-focusing method using image technology[D].Changchun:Graduate School of Chinese Academy of Sciences(Changchun Institute of Optical Precision Machinery and Physics),2013.黄德天.基于图像技术的自动调焦方法研究[D].长春:中国科学院研究生院(长春光学精密机械与物理研究所),2013.
    [8]Wang P J,Chen D J,Wu M L,et al.Implementation of a multiple automatic focusing algorithm for video measuring system[J].China Mechanical Engineering,2007,18(21):2555-2560.王平江,陈德军,巫孟良,等.一种复合的自动对焦方法在影像测量仪中的应用[J].中国机械工程,2007,18(21):2555-2560.
    [9]Jin H Y,Wang Y Y.A fusion method for visible and infrared images based on contrast pyramid with teaching learning based optimization[J].Infrared Physics&Technology,2014,64:134-142.
    [10]Guo J B,Feng H J,Wang L,et al.Design of focusing window based on energy function of gradient[J].Infrared Technology,2016,38(3):197-202.郭敬滨,冯华杰,王龙,等.基于梯度能量函数的调焦窗口构建方法[J].红外技术,2016,38(3):197-202.
    [11]Yao S,Cao D H,Wu Y B.Performance of autofocus judgements in different quantity of information series images[J].Opto-Electronic Engineering,2006,33(5):81-84,90.姚松,曹丹华,吴裕斌.图像信息量的变化对自动对焦评价函数的影响[J].光电工程,2006,33(5):81-84,90.
    [12]Zhang Y T,Ji S P,Wang Q F,et al.Definition evaluation algorithm based on regional contrast[J].Journal of Applied Optics,2012,33(2):293-299.张亚涛,吉书鹏,王强锋,等.基于区域对比度的图像清晰度评价算法[J].应用光学,2012,33(2):293-299.
    [13]Jin W Z,Leng Q J,Zhang Z,et al.Contourlet transform based multiscale image quality assessment metric[J].Journal of Wuhan University(Natural Science Edition),2015,61(2):192-196.金伟正,冷秋君,张卓,等.基于Contourlet变换的多尺度图像质量评价[J].武汉大学学报(理学版),2015,61(2):192-196.
    [14]Wu W,Qiu Z M,Zhao M,et al.Visible and infrared image fusion using NSST and deep Boltzmann machine[J].Optik,2018,157:334-342.
    [15]Wang Y R,Feng H J,Xu Z H,et al.An adjustable coverage range autofocus evaluation function using gradient operator with variable frequency[J].Infrared and Laser Engineering,2016,45(10):1028001.王烨茹,冯华君,徐之海,等.一种覆盖范围可调的变频梯度自动对焦评价函数[J].红外与激光工程,2016,45(10):1028001.

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