Research on far-field spot search and centre location algorithms - Mi, Xiaohong; Sun, Haodong; Liu, Zhaoyu; Han, JinYu (Frontiers in Physics, 2023)
The energy distribution of the far-field spot is uneven and the background is complex. Therefore, identification of far-field points and positioning of the centre is difficult. This article proposes an algorithm for multi-scale Gaussian cyclic convolution for locating the center of far-field spots. First, wavelet denoising is performed on the image of multiple far-field spots, and differential the images of adjacent frames. Then add the absolute values of the difference results. Due to the large size of the far-field spot, the Gaussian distribution of the laser energy is not obvious. Therefore, a multiscale Gaussian convolution kernel is used to perform circular convolution on this images. To preserve low scale Gaussian features, splicing features between two convolutions. In this article, we also design multi-angle combination filters to filter the enhanced Gaussian distribution features. Finally, a fitting of curved polynomials to the reconstructed Gaussian energy distribution to obtain the maximum value, the position where the maximum value is located is the center of the far-field spot. The experiments showed that this method has better robustness.