ICF微靶装配体图像清晰度评价方法

聂凯; 刘文耀; 王晋疆

doi:10.3788/fgxb20143512.1506

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ICF微靶装配体图像清晰度评价方法

发光学应用及交叉前沿 | 更新时间：2020-08-12

- ICF微靶装配体图像清晰度评价方法
- Image Definition Evaluation Method of ICF Micro-target Assembly
- 发光学报 2014年35卷第12期页码：1506-1510
- 作者机构：
  
  天津大学精密仪器与光电子工程学院天津,300072
- 作者简介：
- 基金信息：
  
  国家863计划(2008AA0948)资助项目()
- DOI：10.3788/fgxb20143512.1506
  中图分类号： TP394
- 纸质出版日期：2014-12-3，
  
  收稿日期：2014-8-14，
  
  修回日期：2014-10-11，
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聂凯, 刘文耀, 王晋疆. ICF微靶装配体图像清晰度评价方法[J]. 发光学报, 2014,35(12): 1506-1510

NIE Kai, LIU Wen-yao, WANG Jin-jiang. Image Definition Evaluation Method of ICF Micro-target Assembly[J]. Chinese Journal of Luminescence, 2014,35(12): 1506-1510
聂凯, 刘文耀, 王晋疆. ICF微靶装配体图像清晰度评价方法[J]. 发光学报, 2014,35(12): 1506-1510 DOI： 10.3788/fgxb20143512.1506.

NIE Kai, LIU Wen-yao, WANG Jin-jiang. Image Definition Evaluation Method of ICF Micro-target Assembly[J]. Chinese Journal of Luminescence, 2014,35(12): 1506-1510 DOI： 10.3788/fgxb20143512.1506.

摘要

现有图像清晰度评价函数在对ICF微靶装配体图像的评价过程中

由于不同零件图像对比度的变化

评价函数极易失去其理想曲线特性

导致聚焦精度降低甚至调焦过程失败.针对这一问题

在分析离焦图像模糊原因的基础上

得出离焦图像究其本质为图像结构变化失真.利用Zernike矩具有描述图像结构特征这一特性

提出一种新的针对微靶装配体图像的清晰度评价函数.评价函数由图像不同阶Zernike矩的线性组合构成

通过调节权重系数来实现微靶装配体不同零件图像的清晰度评价.实验结果表明:相较于现有的评价函数

新的评价函数在对微靶装配体图像评价过程中保持了函数的理想曲线特性

尤其是针对低对比度图像

其在灵敏度和抗噪性方面具有明显优势.

Abstract

During the process of evaluating ICF micro-target image with the current image definition evaluation function

owing to the changes in image contrast of different components of micro-target

the evaluation function may lose its ideal curve characteristics easily. This may not only result in the decrease of focus accuracy but also

in some cases

the failure of the entire focusing process. Based on the analysis of the causes for the blurring defocused image

we discovered that the primary reason for defocused image was structural distortion. With the characteristic of Zernike moment of describing the image structure in mind

we propose a new function for evaluating the image definition of micro-target. The new evaluation function is consisted of Zernike moments weighting of different steps

and it is realized through the evaluation of image contrast for micro-targets of different definitions by regulating the weight coefficient. We confirm that the new evaluation function maintains the ideal curve characteristics during the process of evaluating the micro-target images compared to the current evaluation function. In the condition of low contrast

however

the new approach holds a distinct advantage in terms of sensitivity and noise immunity.

关键词

ICF微靶装配体图像清晰度评价函数对比度Zernike矩

Keywords

ICF micro-targetimage definition evaluation functioncontrastZernike moment

references

Wang T. Study on the Key Technologies of Online Monitoring System of Microtarget Assembly [D]. Tianjin: Tianjin University, 2009 (in Chinese).

Wang T, Zhu Y, Yang K M. Structural design and finite element analysis of flexible clamping element [J]. J. Beijing Univ. Technol.(北京工业大学学报), 2012, 38(9):1293-1297 (in Chinese).

Sun Y, Duthaler S, Nelson B J. Autofocusing in computer microscopy: Selecting the optimal focus algorithm [J]. Microscopy Research and Technique, 2004, 65(3):139-149.

Chen C Y, Hwang R C, Chen Y J. A passive auto-focus camera control system [J]. Appl. Soft Comput., 2010, 10(1):296-303.

Pertuz S, Puig D, Garcia M A. Analysis of focus measure operators for shape-from-focus [J]. Pattern Recognition, 2013, 46(5):1415-1432.

Tsai D C, Chen H H. Reciprocal focus profile [J]. IEEE Transaction on Image Processing, 2012, 21(2):459-468.

Fan Y Y, Shen X H, Sang Y J. No reference image sharpness assessment based on contrast sensitivity [J]. Opt. Precision Eng.(光学精密工程), 2011, 19(10):2485-2493 (in Chinese).

Gamadia M, Kehtarnavaz N, Roberts-Hoffman K. Low-light auto-focus enhancement for digital and cell-phone camera image pipelines [J]. IEEE Transaction on Consumer Electronics, 2007, 53(2):249-257.

Xu X, Wang Y, Zhang X, et al. A comparison of contrast measurements in passive autofocus systems for low contrast images [J]. Multimedia Tools and Applications, 2014, 69(1):139-156.

Xu X, Wang Y, Tang J, et al. Robust automatic focus algorithm for low contrast images using a new contrast measure [J]. Sensors, 2011, 11(9):8281-8294.

Wang Z, Bovik A C. Mean squared error: Love it or leave it? A new look at signal fidelity measures [J]. IEEE Signal Processing Magazine, 2009, 26(1):98-117.

Teague M R. Image analysis via the general theory of moments [J]. JOSA, 1980, 70(8):920-930.

Gao S Y, Zhang M Y, Zhang L, et al. Improved algorithm about subpixel edge detection of image based on Zernike orthogonal moments [J]. Acta Automatica Sinica (自动化学报), 2008, 34(9):1163-1168 (in Chinese).

Yousefi S, Rahman M, Kehtarnavaz N. A new auto-focus sharpness function for digital and smart-phone cameras [J]. IEEE Transactions on Consumer Electronics, 2011, 57(3):1003-1009.

Hassen R, Wang Z, Salama M M A. Image sharpness assessment based on local phase coherence [J]. IEEE Transactions on Image Processing, 2013, 22(7):2798-2810.

Brenner J F, Dew B S, Horton J B, et al. An automated microscope for cytologic research a preliminary evaluation [J]. J. Histochem. Cytochem., 1976, 24(1):100-111.

Zhang Y C, Sun Q, Zhao J, et al. Application of depth from defocusing based on logarithmic power spectrum to multi-spectral imager [J]. Opt. Precision Eng.(光学精密工程), 2013, 21(3):767-773 (in Chinese).

Minhas R, Adeel M A, Wu Q M J. Shape from focus using fast discrete curvelet transform [J]. Pattern Recognition, 2011, 44(4):839-853.

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