CN-117291982-B - Moving target positioning method based on single-pixel imaging under complex background

CN117291982BCN 117291982 BCN117291982 BCN 117291982BCN-117291982-B

Abstract

The invention discloses a moving target positioning method based on single-pixel imaging under a complex background, which comprises the steps that under the complex gray background, a target with rapid movement enters a scene, a plurality of binary Fourier base patterns are played by utilizing a digital micromirror device, a light field where the target is positioned is received by a single-point silicon detector after being rapidly modulated, is subjected to analog-digital conversion by a high-speed acquisition card and then is stored in a computer, then partial Fourier coefficients are converted into projection one-dimensional line integral signals in the directions of an x axis and a y axis by utilizing a Fourier slice theorem, the difference of the one-dimensional line integral signals of the target scene is compared in a time dimension, and a coordinate value of the center of the target is determined by utilizing a threshold dividing method.

Inventors

ZHANG WENWEN
ZHANG YANYAN
HE WEIJI
CHEN QIAN

Assignees

南京理工大学

Dates

Publication Date: 20260505
Application Date: 20231016

Claims (6)

1. A moving target positioning method based on single-pixel imaging under a complex background is characterized by comprising the following specific steps: Step 1, obtaining partial Fourier coefficients of a complex background by using a passive single-pixel imaging system; Step 2, acquiring partial Fourier coefficients of a multi-frame moving target image under a complex background by using a single-pixel imaging system; Calculating line integral curves of a complex background image and a multi-frame moving image according to a Fourier slice theorem, wherein the complex scene without a target and part of key frame images are respectively in the complex scene when the target moves in the complex scene The specific formula of the line integral curve in the direction is as follows: Wherein, the Is in the projection direction Shaft and original The included angle of the axes is that, Along the image The projected integral curve in the direction is that, The inverse fourier transform is performed and, Respectively represent background images in The line integral curve in the direction is taken, Indicating that the moving object is at the first At the time of secondary measurement The directional line integral curve is used to determine, Indicating that the moving object is at the first At the time of secondary measurement A directional integral curve; respectively the spatial frequency Is a discretized version of (a); And 4, determining a target motion track according to the complex background image and the line integral curve of the multi-frame motion image, wherein the specific method comprises the following steps: Calculating the abscissa of the center of the object Curve: 。
2. the method for positioning a moving object based on single-pixel imaging under a complex background according to claim 1, wherein the specific method for acquiring the partial fourier coefficient of the complex background by using the single-pixel imaging system is as follows: step 1.1, generating a plurality of gray Fourier base patterns with different spatial frequencies and different initial phases; Step 1.2, up-sampling the gray Fourier substrate pattern, and converting the up-sampled gray Fourier substrate pattern into a binary pattern by using a Floyd-Steinberg error dithering algorithm; Step 1.3, importing a binary pattern into a DMD memory and setting a modulation rate to modulate a scene; step 1.4, synchronously receiving the modulation signal of the complex background reflected light by using a detector and collecting and storing at least 3 light response values by using a digital collecting card; And 1.5, calculating partial Fourier coefficients of the background target image according to at least 3 light response values by using a three-step phase shift formula.
3. The method for positioning a moving object based on single-pixel imaging in a complex background according to claim 2, wherein the gray-scale fourier base pattern is specifically: Wherein, the The spatial coordinates of the images are respectively given, Respectively the spatial frequency In the form of a discretization of the reconstructed image, the size of the reconstructed image is Spatial frequency Is that The values of the discretization are: Spatial frequency Is that The values of the discretization are: , Is the average intensity of the base pattern, Is the modulation amplitude of the signal, Is the initial phase.
4. The method for locating a moving object based on single-pixel imaging in a complex background according to claim 2, wherein the modulated signal of the reflected light of the complex background is obtained by a single-pixel detector The method comprises the following steps: Wherein, the The area where the target is modulated for the fourier base pattern, Is a gray-scale fourier base pattern, Is a target scene image; Photo response value of single pixel detector The method comprises the following steps: Wherein, the For background illumination of the light response value caused at the single pixel detector location, Is a magnification factor.
5. The method for locating a moving object based on single-pixel imaging in a complex background according to claim 2, wherein the specific method for calculating the partial fourier coefficients of the background object image by using a three-step phase shift formula according to at least 3 light response values is as follows: Initial phase of movement Respectively is The corresponding light response values can be respectively ; Calculating Fourier coefficient corresponding to space frequency point by adopting three-step phase shift formula : Corresponding frequency spectrum is complemented by utilizing frequency spectrum symmetry to obtain partial Fourier coefficient of background target image 。
6. The method for positioning a moving object based on single-pixel imaging in a complex background according to claim 1, wherein the specific method for acquiring the partial fourier coefficients of a plurality of frames of moving object images in the complex background by using the single-pixel imaging system is as follows: Step 2.1, setting the DMD picture playing mode as cyclic playing mode Secondary times; Step 2.2, the target translates through the complex background at a constant speed on the electric guide rail, and the detector synchronously receives the modulation signals of the multi-frame moving target reflected light under the complex background and collects and stores the first signal by the digital collecting card Sub-measured light response value , ; Step 2.3 calculating partial Fourier coefficients of the multiple frame moving object image 。

Description

Moving target positioning method based on single-pixel imaging under complex background Technical Field The invention belongs to a moving object tracking and positioning technology, and particularly relates to a moving object positioning method based on single-pixel imaging under a complex background. Background The tracking and imaging of the fast moving object have important application prospects in the fields of navigation, biomedicine, computer vision and the like. Conventional planar array imaging-based target tracking methods rely primarily on photography, capturing images of a target using an image sensor, and further using image post-processing and image analysis algorithms to determine the trajectory of a moving target object in the image. Thus, the accuracy of target tracking is largely dependent on the quality of the captured sequence images and the performance of the algorithm used. Some high performance high speed cameras can capture successive images of high signal-to-noise ratio in a short exposure time. However, in real-time tracking of moving objects, high-speed cameras generally have a huge data throughput, which is proportional to the frame rate of the camera, resulting in excessive hardware requirements in practical applications. In addition, the high-speed camera has excellent performance in the visible light region, but in some invisible light regions, such as infrared wave bands and terahertz wave bands, the performance of the high-speed camera is invalid, so that the application range of the planar array imaging technology in moving object tracking is limited. In recent years, with the development of computational imaging techniques, single-pixel imaging has been widely studied as a novel computational imaging technique that sequentially modulates a light field in which a target object is located by different illumination patterns, records a one-dimensional light intensity signal using a single-pixel sensor without spatial resolution, and then reconstructs an image of the object from the correlation of the illumination patterns and the single-pixel signal. Because the single-pixel detector has the advantages of wide-spectrum imaging, low detector price and the like, the single-pixel imaging shows excellent performance in some invisible wave bands, and therefore, when the single-pixel imaging technology is used for target tracking, the single-pixel imaging technology can work normally in the wave bands where an area-array camera cannot work effectively. Single pixel imaging technology has been widely studied in various fields of moving object tracking and imaging. There are two methods currently available for obtaining the trajectory of a moving object using single pixel imaging. The first method is similar to the planar array imaging method, in that the trajectory of a moving object is analyzed from continuously reconstructed images. However, the frame rate of single pixel imaging is limited by the modulation frequency of the spatial light modulator, while requiring continuous measurement, and thus the number of patterns used in the imaging process is very large. In order to reduce the number of patterns required for imaging, some researchers propose to use a compressed sensing algorithm, but because the compressed sensing algorithm has higher calculation cost and still has larger measurement times, in order to further improve the frame rate, some researchers propose a second method, namely, directly acquiring the track of the moving object without reconstructing the image of the object. The key to this approach is to increase the frame rate by reducing the number of measurement patterns used. Zha et al propose real-time tracking of moving objects at a frequency of 177Hz using 128 Hadamard patterns. Zhang et al utilized 6 fourier base patterns to achieve real-time tracking of a particular type of moving object 1666Hz in two dimensions. Then Zha et al propose a fast moving object tracking method based on geometric moment patterns, realizing a frame rate of 7.4kHz, on the basis of which the team proposes a complementary measurement scheme to increase the frame rate of the method to 11.1kHz. In the same year, xiao et al propose a random moving object imaging method based on geometric moment analysis. The method is to reconstruct the shape and the motion state of a target for the first time under the condition that the translation speed, the translation direction, the rotation center, the rotation speed and the rotation direction are unknown. The method can truly reconstruct a randomly moving object at a rotation speed of 1800 revolutions per minute (r/min). However, the above methods are all high-speed moving object positioning realized in a background-free or pure black background, and the effect of moving object positioning in a complex scene is not clear. The positioning of objects in a real scene mostly needs to be done in a complex background environment without any a priori knowle