In the process of fast automatic alignment of optical path in the integrated diagnosis system of host laser facility, there are six kinds of different optical target images captured. Because of the different characteristics of optical target, different methods for calculating the center of optical target image must be put forward, which increases the algorithm complexity of calculating the optical target center. In order to improve the efficiency and accuracy of fast automatic alignment of laser beam in the integrated diagnosis system, it is necessary and important to propose a method that can calculate all kinds of optical center of collimating images. In this paper, based on the synthesis of the characteristics of pinhole image, schlieren sphere image and common optical target image, a general method for calculating the optical target center of weak contrast collimating image is proposed. Firstly, multi-dimensional image cubes are constructed by using multi time-sharing images or neighborhood vectors, and the dimension of multi-dimensional data cubes is reduced by using NVPCA transformation to remove the correlation between the various dimensional images, separate and readjust the noise of original image; Secondly, the one-dimensional image data is classified by Kmeans, and the binary image is processed by the mathematical morphology operation to separate the laser target and background respectively; Thirdly, if the optical target image is a schlieren image, it need to obtain the background of schlieren image, the region of schlieren sphere, the edge of schlieren sphere respectively; If the optical target image is a pinhole image, it need to obtain the characteristic points on the circle contour of the pinhole image; Finally, the least square method is used to calculate the circle center of the pinhole image and the schlieren sphere image, and the center of gravity method is used to calculate the center of optical target. The experimental results show that this paper synthesizes the same and different characteristics of all kinds of collimating images, proposes a method to calculate the optical target center of weak contrast collimating images, improves the calculation accuracy of the optical target center of collimating images (less than 1 pixel) effectively, shortens the fast alignment time of the optical path of the integrated diagnosis system, and provides an effective guarantee for the measurement experiment of far-field focal spot of high power laser based on schlieren method.
[1]
Ji Jian-wei.
Application of chain codes table and line segment table in computer image processing
,
2007
.
[2]
Tan Yu.
Algorithm of laser spot detection based on circle fitting
,
2002
.
[3]
Wei Wang,et al.
[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].
,
2011,
Guang pu xue yu guang pu fen xi = Guang pu.
[4]
高敏 Gao Min,et al.
Detection of infrared dim small target based on image patch contrast
,
2015
.
[5]
王伟 Wang Wei,et al.
A Method for Detecting Small and Weak Defect Targets Based on Neighborhood Vector PCA Image Enhancement
,
2019
.
[6]
Zhang Bing,et al.
Research of hyperspectral target detection algorithms based on variance minimum
,
2010
.
[7]
Hongguang Li,et al.
Method for measuring laser spot center based on multi-dimensional reconstruction in integrated diagnostic system
,
2015
.