X-ray imaging of fast dynamics with single-pixel detector

Sefi, O.; Klein, Yishay; Strizhevsky, E.; Dolbnya, Igor P.; Shwartz, Sharon

doi:10.1364/oe.396497

Cited by 15 publications

(8 citation statements)

References 39 publications

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“…Our approach is related to the quasi-thermal ghost imaging (GI) approach, which has been investigated extensively in a broad range of wavelengths (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32) from radio waves (30) to x-rays (17)(18)(19)(20)(21)(22)(23)(24), and even with atoms (33), neutrons (34), and electrons (35). GI can be used for the reconstruction of two-dimensional and three-dimensional images (16,24), and by using CS (28) or AI (29) the measurement time can be reduced significantly.…”

mentioning

confidence: 99%

Chemical element mapping by x-ray computational ghost fluorescence

Klein

Sefi

Schwartz

et al. 2022

Optica

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Chemical element mapping is an imaging tool that provides essential information on composite materials and it is crucial for a broad range of fields ranging from fundamental science to numerous applications. Methods that exploit x-ray fluorescence are very advantageous and are widely used, but require focusing of the input beam and raster scanning of the sample. Thus the methods are slow and exhibit limited resolution due to focusing challenges. We demonstrate a new focusing free x-ray fluorescence method based ghost imaging that overcomes those limitations. We combine our procedure with compressed sensing to reduce the measurement time and the exposure to radiation by more than 80%. Since our method does not require focusing, it opens the possibility for improving the resolution and image quality of chemical element maps with tabletop x-ray sources and for extending the applicability of x-ray fluorescence detection to new fields such as medical imaging and homeland security applications.

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mentioning

confidence: 99%

Chemical element mapping by x-ray computational ghost fluorescence

Klein

Sefi

Schwartz

et al. 2022

Optica

Self Cite

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“…Then the working range of M can be recorded. In this experiment, T ≈ 6 (pixel), so M can be set within [1,6] (pixel). In this experiment, in order to obtain a qualified result, we set the largest M as 4.…”

Section: Real Experimentsmentioning

confidence: 99%

“…Single-pixel imaging (SPI) is one of the computational imaging methods [1][2][3][4], which has attracted much attention due to its excellent capabilities for imaging applications with limited data transmission bandwidth or non-visible light imaging [5][6][7]. A SPI system often works by projecting a series of sampling patterns to a target scene first, then capturing the light intensity of the scene successively using a single-pixel detector (SPD), and finally reconstructing the target scene from the captured data sequence.…”

Section: Introductionmentioning

confidence: 99%

3d Single-Pixel Imaging with Active Sampling Patterns and Learning Based Reconstruction

Ma¹,

Wang²

2022

SSRN Journal

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“…The proportions of 0 and 1 in the used random 0/1 patterns are 50% and 50%, respectively. The CS algorithm used in this paper is the TVAL3 (Total Variation Augmented Lagrangian Alternating-direction Algorithm) algorithm [34,35]. The signal to noise ratio (SNR), peak signal to noise ratio (PSNR), correlation coefficient (CC), and structural similarity index measure (SSIM) values are used to evaluate the image quality.…”

Section: A Without Noisementioning

confidence: 99%

Sequential Subtraction-Based Compressive Single-Pixel Imaging in Complicate Ambient Light

Wang

2022

IEEE Photonics J.

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As a special imaging technique, one of the most important advantages of single-pixel imaging (SPI) than conventional imaging method is that it can recover the object image even through turbid medium. In these situations, the noises bring by the turbid medium usually obey special rules in statistics. While in some other applications, SPI is performed in the environment with complicate ambient light, in which no prior information of the environment noise is known. Aiming at this situation, in this work, the frame-by-frame subtraction-based compressive sensing SPI (FFS-CSPI) method with random 0/1 pattern is used to decrease the effect from the unknown ambient light. The noise robustness of the FFS-CSPI method is analyzed and compared with Hadamard CSPI. In simulation and experiment, two kinds of noises, from external light source and from background video, are considered. The results prove that FFS-CSPI with random 0/1 patterns can achieve higher image quality than conventional mean subtraction method and Hadamard CSPI with the same measurement number. Considering the high refresh rate of digital micromirror device when it loads the 0/1 binary patterns, the imaging speed is acceptable. This work will promote the practical applications of SPI in complicated environment.

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X-ray imaging of fast dynamics with single-pixel detector

Cited by 15 publications

References 39 publications

Chemical element mapping by x-ray computational ghost fluorescence

Chemical element mapping by x-ray computational ghost fluorescence

3d Single-Pixel Imaging with Active Sampling Patterns and Learning Based Reconstruction

Sequential Subtraction-Based Compressive Single-Pixel Imaging in Complicate Ambient Light

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