Laser detection system for three-dimensional imaging of moving object and imaging method

Abstract

The invention provides a laser detection system for three-dimensional imaging of a moving object and an imaging method. The imaging method comprises the following steps that object slice images are obtained through the laser detection system; a reference image is selected from the object slice images; mutual information registration is conducted on the reference image and an image to be registered; whether the registration succeeds or not is judged, the offset amount and rotating amount of the image to be registered with respect to the reference image are output if the registration succeeds, the image to be registered is corrected according to the offset amount and the rotating amount to achieve space consistency between the image to be registered and the reference image, and a particle swarm search algorithm is continuously adopted to optimize the offset amount and rotating amount and transform the image to be registered if the registration does not succeed; time delay of each pixel point in the area where the object is located is calculated; corresponding distance information is calculated by adopting a mutual correlation algorithm; the distance information corresponding to each pixel is directly converted into a three-dimensional image of the object. For the moving object, the slice images different in gating distance are utilized, the imaging difficulty of the moving object is greatly reduced, and the application range for a high-speed object is wider.

Description

technical field [0001] The invention belongs to the technical field of laser imaging detection, and relates to a laser detection system and an imaging method for three-dimensional imaging of a moving target. Background technique [0002] Three-dimensional imaging is an effective means to distinguish the attitude of objects and identify true and false targets. In range-gated laser active imaging, for a stationary target, target images at different gating distances can be obtained by imaging target slices, and then a three-dimensional image of the target can be obtained through an algorithm. For a moving target, the spatial position of the target will change during slice imaging, so it is necessary to register the target images with different gating distances so that the spatial position of the target is basically aligned, and then the 3D image of the target can be obtained . [0003] Two of the key technologies are laser image registration and 3D reconstruction algorithms. ...

AI Technical Summary

Problems solved by technology

The binarization algorithm has a great dependence on the selection of the threshold value. Whether the threshold value is suitable or not is directly related to the segmentation and extraction of the target. When the noise is large or the image target is not obvious, it makes it difficult for the 3D image to reflect the actual structural features.

In the centroid algorithm, it is assumed that each pixel value has a gray peak corresponding to it, but in actual imaging, the gray value of each pixel does not have a one-to-one correspondence with the distance value, and the gray value has a flat top phenomenon. In addition, due to noise and Due to the influence of the atmosphere, there may be multiple peaks in the gray value, and the maximum gray value corresponds to the imaging time of multiple slices, so the distance value cannot be calculated using the centroid method

Images