Transmissive Single-Pixel Microscopic Imaging through Scattering Media

Deng, Huaxia; Wang, Guan; Li, Qiang; Sun, Qianzhen; Zhong, Xiaoming

doi:10.3390/s21082721

Cited by 14 publications

(4 citation statements)

References 54 publications

(34 reference statements)

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“…The evaluation index of the model is an index system used to measure the performance of the model, which is used to evaluate the performance of the model on specific tasks, such as precision (P), recall (R), mean average precision (mAP), detection speed, and model size, etc. The calculation formula for precision can be calculated using Equation (10):…”

Section: The Evaluation Indexmentioning

confidence: 99%

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Research on Abrasive Particle Target Detection and Feature Extraction for Marine Lubricating Oil

Bai,

Ding,

Zhang

et al. 2024

JMSE

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The hydraulic oil of marine equipment contains a large number of abrasive contaminants that reflect the operating condition of the equipment. In order to realize the detection of particulate contaminants, this research first proposes a shape-based classification method for oil abrasive particles, designs an oil abrasive particle collection system, and constructs a new dataset. After that, the research introduces deep learning target detection technology in computer vision, and uses GhostNet to lighten the network structure, the CBAM (Convolutional Block Attention Module) attention mechanism to improve the generalization ability of the model, and the ASPP module to enhance the model sensory wildness, respectively. A lightweight target detection model, WDD, is created for the identification of abrasive particles. In this study, the WDD model is tested against other network models, and the mAP value of WDD reaches 91.2%, which is 4.8% higher than that of YOLOv5s; in addition, the detection speed of the WDD model reaches 55 FPS. Finally, this study uses real ship lubricating oils for validation, and the WDD model still maintains a high level of accuracy. Therefore, the WDD model effectively balances the accuracy and detection speed of marine oil abrasive particle detection, which is superior to other oil abrasive particle detection techniques.

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Section: The Evaluation Indexmentioning

confidence: 99%

“…The microscopic imaging method places a slide containing an oil abrasive sample under an optical microscope for observation during testing and then hands it over to a computer for subsequent analysis and processing [10]. Compared to iron spectrum analysis, microscopic imaging has a simpler experimental environment.…”

Section: Introductionmentioning

confidence: 99%

Research on Abrasive Particle Target Detection and Feature Extraction for Marine Lubricating Oil

Bai,

Ding,

Zhang

et al. 2024

JMSE

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show abstract

“…Ghost imaging (GI) relies on calculating the correlation function using structured patterns that illuminate an object and the overall light intensity transmitted through it. 1 Currently, this technique finds active application in diverse fields such as remote sensing, [2][3][4][5] microbiological and medical research, 6,7 and noise-resistant data transmission [8][9][10][11][12] and processing 13 systems. GI techniques are being developed and used in various frequency ranges: in the visible, 4 infrared 14 and terahertz (THz) 15 ones.…”

Section: Introductionmentioning

confidence: 99%

Ghost imaging with auxiliary multiplex channels: a review of the latest results

Petrov,

Ismagilov,

Oparin

et al. 2024

Speckle 2023: VIII International Conference on Speckle Metrology

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In this paper, we present a review of the latest results obtained in the scope of ghost imaging using auxiliary multiplex channels. The proposed methods make it possible to increase the speed of image acquisition, as well as eliminate distortions in the signal of a bucket detector. One of the most serious limitations of ghost imaging is the large number of measurements required. During the data acquisition, the optical environment where the observation object is located may change its parameters, which will negatively affect the quality of the reconstructed image. To solve these problems, it is possible to use fast spatial light modulators to set structured patterns and fast detectors. However, such equipment is not available in some spectral ranges and is not able to suppress distortions in the detected signal. In this regard, our team has proposed a number of techniques to solve the problems of a large number of measurements and non-stationarity of the optical medium in ghost imaging systems. First of all, an auxiliary polarization channel method was presented in a ghost imaging system to eliminate distortion in the signal of a bucket detector. Secondly, wavelength multiplexing methods have been proposed in the visible and terahertz wavelength ranges. These methods will make ghost imaging systems more applicable to the tasks of remote sensing and mapping of areas in various spectral ranges.

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“…Thus, to improve the imaging resolution, the integration of the detector needs to be increased, which leads to higher requirements for manufacturing. Single-pixel imaging (SPI) [ 1 , 2 ] uses a single-pixel detector, instead of a detector array with a lot of pixels in traditional imaging, to realize two-dimensional or even multi-dimensional imaging, which gives cost-efficiency to broadband imaging and resolution enhancement, and recently has a lot of attention with the potential of applications in various imaging areas such as visible range imaging [ 3 ], multispectral imaging [ 4 , 5 , 6 , 7 ], hyperspectral imaging [ 8 ], ultrafast imaging [ 9 ], infrared imaging [ 10 ], terahertz imaging [ 11 , 12 , 13 ], gas imaging [ 14 ], microscopic imaging [ 15 , 16 , 17 ], imaging through scattering media [ 18 , 19 ], photoacoustic imaging [ 20 ], long-range imaging [ 21 , 22 ], X-ray imaging [ 23 , 24 ], 3D imaging [ 25 ] and holography [ 26 ], etc.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Common Algorithms for Single-Pixel Imaging via Compressed Sensing

Zhao

Gao

Zhai

et al. 2023

Sensors

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Single-pixel imaging (SPI) uses a single-pixel detector instead of a detector array with a lot of pixels in traditional imaging techniques to realize two-dimensional or even multi-dimensional imaging. For SPI using compressed sensing, the target to be imaged is illuminated by a series of patterns with spatial resolution, and then the reflected or transmitted intensity is compressively sampled by the single-pixel detector to reconstruct the target image while breaking the limitation of the Nyquist sampling theorem. Recently, in the area of signal processing using compressed sensing, many measurement matrices as well as reconstruction algorithms have been proposed. It is necessary to explore the application of these methods in SPI. Therefore, this paper reviews the concept of compressive sensing SPI and summarizes the main measurement matrices and reconstruction algorithms in compressive sensing. Further, the performance of their applications in SPI through simulations and experiments is explored in detail, and then their advantages and disadvantages are summarized. Finally, the prospect of compressive sensing with SPI is discussed.

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Transmissive Single-Pixel Microscopic Imaging through Scattering Media

Cited by 14 publications

References 54 publications

Research on Abrasive Particle Target Detection and Feature Extraction for Marine Lubricating Oil

Research on Abrasive Particle Target Detection and Feature Extraction for Marine Lubricating Oil

Ghost imaging with auxiliary multiplex channels: a review of the latest results

Comparison of Common Algorithms for Single-Pixel Imaging via Compressed Sensing

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