Image reconstruction of dynamic infrared single-pixel imaging system

Tong, Qi; Jiang, Yilin; Wang, Haiyan; Guo, Limin

doi:10.1016/j.optcom.2017.09.069

Cited by 13 publications

(4 citation statements)

References 17 publications

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“…Research interest is now focusing on the motion problems associated with foreground targets and compressive imaging systems. [14][15][16][17] Tong Q. et al reconstructed an image in the infrared (IR) rosette scanning system by analyzing the relationship between the target image and the scene in each frame. 15 Jiao S. et al solved the problem of dynamic compressive sampling using prior knowledge of the target motion type and the ultrafast structured illumination.…”

Section: Introductionmentioning

confidence: 99%

Modeling and image quality enhancement for dynamic compressive imaging system

Zha

Zhang

Duan

2021

Journal of Algorithms & Computational Technology

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Traditional single-pixel imaging systems are aimed mainly at relatively static or slowly changing targets. When there is relative motion between the imaging system and the target, sizable deviations between the measurement values and the real values can occur and result in poor image quality of the reconstructed target. To solve this problem, a novel dynamic compressive imaging system is proposed. In this system, a single-column digital micro-mirror device is used to modulate the target image, and the compressive measurement values are obtained for each column of the image. Based on analysis of the measurement values, a new recovery model of dynamic compressive imaging is given. Differing from traditional reconstruction results, the measurement values of any column of vectors in the target image can be used to reconstruct the vectors of two adjacent columns at the same time. Contingent upon characteristics of the results, a method of image quality enhancement based on an overlapping average algorithm is proposed. Simulation experiments and analysis show that the proposed dynamic compressive imaging can effectively reconstruct the target image; and that when the moving speed of the system changes within a certain range, the system reconstructs a better original image. The system overcomes the impact of dynamically changing speeds, and affords significantly better performance than traditional compressive imaging.

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Section: Introductionmentioning

confidence: 99%

Modeling and image quality enhancement for dynamic compressive imaging system

Zha

Zhang

Duan

2021

Journal of Algorithms & Computational Technology

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“…An infrared imaging system usually faces a complex and difficult working environment. For example, military UAVs (unmanned aerial vehicles) or precision strike weapons may be disturbed by air turbulence in flight, causing infrared detectors to experience large torque or high-frequency vibration in the imaging process, thus resulting in blurred, distorted, or ghosting images from which the target information cannot be effectively obtained [1][2][3][4]. Therefore, it is urgent to introduce an image stabilization mechanism in the imaging system to compensate for the imaging error and improve the imaging accuracy.…”

Section: Introductionmentioning

confidence: 99%

Design, Analysis and Experiment of a Bridge-Type Piezoelectric Actuator for Infrared Image Stabilization

et al. 2021

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Piezoelectric actuators are widely used in the optical field due to their high precision, compact structure, flexible design, and fast response. This paper presents a novel piezoelectric actuator with a bridge-type mechanism, which can be used to stabilize the images of an infrared imaging system. The bridge amplification mechanism is used to amplify the actuation displacement, and its structural parameters are optimized by the response surface method. The control strategy of the image stabilization system is formulated, and the overall structure of the infrared image stabilization system is designed according to the principle of image stabilization and the control strategy. The prototype was fabricated and verified by a series of experiments. In the test, the laminated piezoelectric ceramics are used as the driving element, and its maximum output displacement was about 17 μm under a voltage of 100 V. Firstly, the performance of the piezoelectric amplification mechanism was tested, and the maximum displacement of the piezoelectric micro-motion mechanism was 115 μm. The displacement amplification ratio of the mechanism was 5.7. Then, the step distance and response time of the micro-displacement mechanism were measured by inputting the stepping signal. When the input voltage increased to 3 V, 5 V, and 7 V, the stepping displacements of the mechanism were 2.4 μm, 4.1 μm, and 5.8 μm. Finally, the image stabilization effect of the designed mechanism was verified by imaging timing control and feedback signal processing.

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“…Single photon compressive imaging [1][2][3] is a technique using photon counting for ultra-weak light imaging based on the compressed sensing (CS) theory [4][5][6][7]. Single photon compressive imaging combines the advantages of single-pixel imaging [8][9][10][11][12], which can solve the problem of insufficient pixel size of existing single photon detectors and obtain higher imaging sensitivity. The ultra-high sensitivity of single photon compressive imaging can be achieved at the ultra-weak light level.…”

Section: Introductionmentioning

confidence: 99%

Single Photon Compressive Imaging Based on Digital Grayscale Modulation Method

et al. 2020

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In single-pixel imaging or computational ghost imaging, the measurement matrix has a great impact on the performance of the imaging system, because it involves modulation of the optical signal and image reconstruction. The measurement matrix reported in the existing literatures is first binarized and then loaded onto the digital micro-mirror device (DMD) for optical modulation, that is, each pixel can only be modulated into on-off states. In this paper, we propose a digital grayscale modulation method for more efficient compressive sampling. On the basis of this, we demonstrate a single photon compressive imaging system. A control and counting circuit, based on field-programmable gate array (FPGA), is developed to control DMD to conduct digital grayscale modulation and count single-photon pulse output from the photomultiplier tube (PMT) simultaneously. The experimental results show that the imaging reconstruction quality can be improved by increasing the sparsity ratio properly and compressive sampling ratio (SR) of these gray-scale matrices. However, when the compressive SR and sparsity ratio are increased appropriately to a certain value, the reconstruction quality is usually saturated, and the imaging reconstruction quality of the digital grayscale modulation is better than that of binary modulation.

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Image reconstruction of dynamic infrared single-pixel imaging system

Cited by 13 publications

References 17 publications

Modeling and image quality enhancement for dynamic compressive imaging system

Modeling and image quality enhancement for dynamic compressive imaging system

Design, Analysis and Experiment of a Bridge-Type Piezoelectric Actuator for Infrared Image Stabilization

Single Photon Compressive Imaging Based on Digital Grayscale Modulation Method

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