Large-area single photon compressive imaging based on multiple micro-mirrors combination imaging method

Yan, Qiurong; Wang, Hui; Yuan, Chenglong; Li, Bing; Wang, Yuhao

doi:10.1364/oe.26.019080

Cited by 11 publications

(4 citation statements)

References 23 publications

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“…If each micro-mirror is defined as one pixel, the imaging resolution of the whole DMD work area is 1024 × 768 pixel. In order to obtain a low resolution image of 32 × 32 pixels as a priori information before adaptive measurement, a multiple micro-mirrors combination imaging method is adopted [29]. As shown in Fig.…”

Section: Iterative Adaptive Compressive Sensing Measurement Methodsmentioning

confidence: 99%

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Iterative Adaptive Photon-Counting Compressive Imaging Based on Wavelet Entropy Automatic Threshold Acquisition

et al. 2019

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We demonstrate an iterative adaptive photon-counting compressive imaging system. The low-resolution image obtained from the previous sampling are used to calculate the wavelet coefficients. A method based on multiple micro-mirrors combination is proposed to conduct iterative adaptive sampling on the imaging regions corresponding to important children wavelet coefficients at all levels. In order to reconstruct a better quality image directly with appropriate compression ratio and time and avoid speculative selection of thresholds, an automatic threshold acquisition method based on wavelet entropy is proposed, which can automatically follows the change of the object image to obtain the threshold. The iterative adaptive compressive sensing measurement method based on wavelet entropy automatic threshold acquisition is applied to photon-counting compressive imaging system. Experimental results show that a high resolution image can be reconstructed with low compression ratio and short time in extremely low light environment, the quality of reconstructed images of iterative adaptive compressive sensing measurement is better than that of adaptive basis scan.

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Section: Iterative Adaptive Compressive Sensing Measurement Methodsmentioning

confidence: 99%

“…This is because the simulation of Poisson noise adopts Monte Carlo simulation instead of numerical simulation. And the magnitude of Poisson noise is equal to sqrt(N), where N is the photon number [29]. As the mean of Poisson noise increases, the number of photons must be increased.…”

Section: Iterative Adaptive Compressive Sensing Measurement Methodsmentioning

confidence: 99%

Iterative Adaptive Photon-Counting Compressive Imaging Based on Wavelet Entropy Automatic Threshold Acquisition

et al. 2019

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“…This scheme has been described in detail in Ref. [35]. Different kinds of measurement matrix corresponding to fewer-pixels imaging is constructed as follow.…”

Section: Construction Of Measurement Matrix and Theoretical Analysismentioning

confidence: 99%

Measurement Matrix Construction for Large-area Single Photon Compressive Imaging

Wang

Yan

et al. 2019

Sensors

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We have developed a single photon compressive imaging system based on single photon counting technology and compressed sensing theory, using a photomultiplier tube (PMT) photon counting head as the bucket detector. This system can realize ultra-weak light imaging with the imaging area up to the entire digital micromirror device (DMD) working region. The measurement matrix in this system is required to be binary due to the two working states of the micromirror corresponding to two controlled elements. And it has a great impact on the performance of the imaging system, because it involves modulation of the optical signal and image reconstruction. Three kinds of binary matrix including sparse binary random matrix, m sequence matrix and true random number matrix are constructed. The properties of these matrices are analyzed theoretically with the uncertainty principle. The parameters of measurement matrix including sparsity ratio, compressive sampling ratio and reconstruction time are verified in the experimental system. The experimental results show that, the increase of sparsity ratio and compressive sampling ratio can improve the reconstruction quality. However, when the increase is up to a certain value, the reconstruction quality tends to be saturated. Compared to the other two types of measurement matrices, the m sequence matrix has better performance in image reconstruction.

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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.…”

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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Large-area single photon compressive imaging based on multiple micro-mirrors combination imaging method

Cited by 11 publications

References 23 publications

Iterative Adaptive Photon-Counting Compressive Imaging Based on Wavelet Entropy Automatic Threshold Acquisition

Iterative Adaptive Photon-Counting Compressive Imaging Based on Wavelet Entropy Automatic Threshold Acquisition

Measurement Matrix Construction for Large-area Single Photon Compressive Imaging

Single Photon Compressive Imaging Based on Digital Grayscale Modulation Method

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