Self-adaptive multi-scale three-dimensional ghost imaging method

Abstract

The invention discloses a self-adaptive multi-scale three-dimensional ghost imaging method. The method comprises the following steps: firstly, obtaining low-resolution ghost images of a target in different directions through a ghost imaging system; preprocessing an image result obtained at a low sampling rate, and filtering out noise; calculating a target surface normal vector by using the preprocessed two-dimensional ghost image; taking the sparsity of the surface normal vector as a standard division region for dividing the high-resolution region and the low-resolution region; generating a high-resolution imaging reference light field according to the divided high-resolution area, and obtaining a high-resolution ghost image; and finally, splicing the images of the high-resolution area andthe low-resolution area, and performing three-dimensional reconstruction to obtain a target three-dimensional image. The sampling frequency of the ghost imaging system is reduced, and the operation speed of the system is improved; measurement data of three-dimensional imaging is reduced, data redundancy is reduced, and transmission and storage of the data are facilitated.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional imaging, in particular to an adaptive multi-scale three-dimensional ghost imaging method. Background technique [0002] Ghost imaging (GI), also known as correlated imaging or two-photon imaging, is an imaging technology that has attracted much attention and is different from traditional imaging concepts. There are two optical paths in the ghost imaging system, a signal optical path and a reference optical path. In the signal light path, a barrel detector is used to detect the total light intensity passing through the target object. In the reference light path, however, a detector with spatial resolution is used to detect the spatial intensity distribution of the light source. The image is reconstructed by cross-correlating the light intensities detected by the two detectors. Computational ghost imaging is an improved ghost imaging technology, which combines light modulation devices s...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide an adaptive multi-scale 3D ghost imaging method, which solves the technical problem that ghost imaging requires a large amount of sampling data to reconstruct a high-resolution 3D image of the target, and can ease the gap between resolution and sampling rate. contradiction

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