High-precision method for quickly positioning centers of two-dimensional Gaussian distribution spot images

Abstract

The invention relates to a high-precision method for quickly positioning centers of two-dimensional Gaussian distribution spot images, which includes obtaining an approximate two-dimensional Gaussian distribution image through defocused imaging of a CCD (charge coupled device) camera, processing the image to preliminarily split multiple light spots in the image and mark serial numbers, determining the integer pixel coordinate of the light spot center before setting up local image coordinate system with the integer pixel coordinate serving as an origin, calculating variance of the Gaussian light spot and sub-pixel coordinate components of the light spot center in the x and y directions, and compositing the integer pixel coordinate with the sub-pixel coordinate to obtain the actual precise coordinate of the light spot center. All pixel grayscale information in a window is comprehensively utilized by the method, position of the sub-pixel center of the Gaussian distribution light spot canbe directly calculated through an analytic expression, solving of a generalized inverse matrix is not needed, efficiency is improved by more than 200 times and precision loss is avoided as compared with those of the traditional Gaussian quadrics fitting method, and real-time extracting of multiple light spot centers can be realized.

Description

technical field [0001] The invention relates to a fast and high-precision positioning method for the center of a two-dimensional Gaussian distribution light spot image, which can be used in the fields of visual measurement, astronomical navigation, astronomical observation, etc., and belongs to the cross field of measurement / testing and digital image processing. Background technique [0002] Gaussian distribution spot image center positioning has a wide range of applications in visual measurement, astronomical navigation, astronomical observation and other fields, among which the most typical applications are star sensors and light pen visual coordinate measurement systems. The star sensor is a high-precision attitude monitoring device with the star as the reference system and the starry sky as the working object, which can provide accurate space orientation and reference for satellites, intercontinental strategic missiles, spacecraft, etc. The optical pen-type visual coordi...

AI Technical Summary

Problems solved by technology

For spot images whose gray distribution is known to be Gaussian, the Gaussian surface fitting method is the most accurate method, but this algorithm needs to solve the generalized inverse matrix and more logarithmic operations, so the operation process is complicated and the program operation efficiency Low, unable to meet the real-time requirements of the current satellite navigation, multi-target dynamic tracking measurement and other applications for the algorithm

The gray-scale centroid method and the weighted gray-scale centroid method are commonly used in the general positioning of the spot center. The calculation process is simple and the operation efficiency is high. However, for the spot image with Gaussian distribution, the accuracy is lower than that of the Gaussian surface fitting method, which is difficult to meet the requirements of current satellite navigation. , visual measurement and other fields of precision requirements

The paraboloid fitting method is a simplified algorithm of the Gaussian surface fitting method, the efficiency is slightly improved, but the accuracy is significantly lower than the Gaussian surface fitting method

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