Image-based autofocusing algorithm applied in image fusion process for optical microscope

This study proposes a novel passive auto-focusing algorithm which is applied in the optical microscope. The main core of the proposed auto-focusing algorithm is the weight distribution of Gaussian pyramid and the zero weight values in the designed median mask. It is robust for the noise problem. The optical microscope measurement is one of non-contact optical measurement technology. The captured images will be blurred when the depth of the sample exceeds the depth of field in the microscope. The blurred area in the image easily produces the noise. In order to reduce the problems of the image blurring and the noise, the proposed auto-focusing algorithm is applied in the process of image fusion algorithm. The stack of the images is captured by the microscope system which contains the CCD (i.e. Charge-coupled devices) and the PZT (i.e. piezoelectric transducer). The stack of images contains the clear image on the focal plane and the blurred image out of the depth of field. The process of the image fusion algorithm calculates this stack of the images to obtain the 2D fusion image and the 3D profile, simultaneously. The proposed algorithm is compared to the known four autofocusing algorithms. In the experiment results of the 2D fusion image, the proposed algorithm is as good as the four auto-focusing algorithms. Moreover, in the results of 3D profile, the RMSE error of the proposed algorithm is 287.628, which is lower than the other RMSE errors of the four auto-focusing algorithms.

[1]  P. Cheng,et al.  Image reconstruction based on tuning depth focus by PZT , 2020, 2020 Opto-Electronics and Communications Conference (OECC).

[2]  Y. Takai,et al.  Development of a real-time wave field reconstruction TEM system (I): incorporation of an auto focus tracking system. , 2017, Microscopy.

[3]  Jingwen Yan,et al.  High quality multi-focus image fusion using self-similarity and depth information , 2015 .

[4]  Bo Liu,et al.  An auto-focus algorithm based on maximum gradient and threshold , 2012, 2012 5th International Congress on Image and Signal Processing.

[5]  Bo Liu,et al.  Research and Realization of an Anti-noise Auto-focusing Algorithm , 2012, 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics.

[6]  Wencheng Wang,et al.  A Multi-focus Image Fusion Method Based on Laplacian Pyramid , 2011, J. Comput..

[7]  Ran Zeimer,et al.  An Image Based Auto-Focusing Algorithm forDigital Fundus Photography , 2009, IEEE Transactions on Medical Imaging.

[8]  Zhongliang Jing,et al.  Evaluation of focus measures in multi-focus image fusion , 2007, Pattern Recognit. Lett..

[9]  Bradley J Nelson,et al.  Autofocusing in computer microscopy: Selecting the optimal focus algorithm , 2004, Microscopy research and technique.

[10]  D. Vollath Automatic focusing by correlative methods , 1987 .