Experimental Research on Pseudo-Thermal Light Ghost Imaging with Random Phase Plate Based on Variable Motion Trail

Nan, 吴楠 Wu; Wenlin, 龚文林 Gong; Shensheng, 韩申生 Han

doi:10.3788/aos201535.0711005

Cited by 2 publications

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“…The key of the technique is to accurately address incident positions on a diffuser by a high-precision motor to produce repeatable pseudo-thermal speckle patterns. All reference intensity distributions are recorded in a low speed in advance, eliminating the camera recording in the imaging process [51][52][53].…”

Section: A Fast Sampling Methodsmentioning

confidence: 99%

A Review of Ghost Imaging via Sparsity Constraints

Han

Shen

et al. 2018

Applied Sciences

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Different from conventional imaging methods, which are based on the first-order field correlation, ghost imaging (GI) obtains the image information through high-order mutual-correlation of light fields from two paths with an object appearing in only one path. As a new optical imaging technology, GI not only provides us new capabilities beyond the conventional imaging methods, but also gives out a new viewpoint of imaging physical mechanism. It may be applied to many potential applications, such as remote sensing, snap-shot spectral imaging, thermal X-ray diffraction imaging and imaging through scattering media. In this paper, we reviewed mainly our research work of ghost imaging via sparsity constraints (GISC) and discussed the application and theory prospect of GISC concisely.

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Section: A Fast Sampling Methodsmentioning

confidence: 99%

A Review of Ghost Imaging via Sparsity Constraints

Han

Shen

et al. 2018

Applied Sciences

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Fractal Dimension of Fractional Brownian Motion Based on Random Sets

Chai

2020

Fractals

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The fractal dimension of fractional Brownian motion can effectively describe random sets, reflecting the regularity implicit in complex random sets. Data mining algorithms based on fractal theory usually follow the calculation of the fractal dimension of fractional Brownian motion. However, the existing fractal dimension calculation methods of fractal Brownian motion have high time complexity and space complexity, which greatly reduces the efficiency of the algorithm and makes it difficult for the algorithm to adapt to high-speed and massive data flow environments. Therefore, several existing fractal dimension calculation methods of fractional Brownian motion are summarized and analyzed, and a random method is proposed, which uses a fixed memory space to quickly estimate the associated dimension of the data stream. Finally, a comparison experiment with existing algorithms proves the effectiveness of this random algorithm. Second, in the sense of two different measures, based on the principle of stochastic comparison, the stability of the stochastic fuzzy differential equations is derived using the stability of the comparison equations, and the practical stability criterion of two measures according to probability is obtained. Then, the stochastic fuzzy differential equations are discussed. The definition of stochastic exponential stability is given and the stochastic exponential stability criterion is proved.

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Experimental Research on Pseudo-Thermal Light Ghost Imaging with Random Phase Plate Based on Variable Motion Trail

Cited by 2 publications

References 0 publications

A Review of Ghost Imaging via Sparsity Constraints

A Review of Ghost Imaging via Sparsity Constraints

Fractal Dimension of Fractional Brownian Motion Based on Random Sets

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