Depolarization Characteristics of Different Reflective Interfaces Indicated by Indices of Polarimetric Purity (IPPs)

Li, Dekui; Guo, Kai; Sun, Yongxuan; Bu, Xiang; Gao, Jun; Guo, Zhongyi

doi:10.3390/s21041221

Cited by 15 publications

(2 citation statements)

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“…In general, fully polarized light gets depolarized when it transmits through a scattering environment [ 31 , 32 ]. While DOP of a fully polarized light is 1 and is 0 for unpolarized light, DOP for a partially polarized light is between 0 and 1.…”

Section: Methodsmentioning

confidence: 99%

Stokes–Mueller polarization-based analysis of model SARS-CoV-2 virions

et al. 2023

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Understanding the virology of the coronavirus at the structural level has gained utmost importance to overcome the constant and long-term health complications induced by them. In this work, the light scattering properties of SARS-CoV-2 of size 140 nm were simulated by using discrete dipole approximation (DDA) for two incident wavelengths 200 nm and 350 nm, respectively. Three different 3-dimensional (3D) models of SARS-CoV-2 corresponding to 15, 20, and 40 numbers of spike proteins on the viral capsid surface were constructed as target geometries for the DDA calculations. These models were assessed by employing Stokes–Mueller polarimetry to obtain individual polarization properties such as degree of polarization (DOP), degree of linear polarization (DOLP), and degree of circular polarization (DOCP). Irrespective of its spike numbers, all the coronavirus models were found to display higher DOP and DOCP values and negligibly small DOLP values for circularly polarized incident light, indicating the presence of chiral structures. On the other hand, the lack of understanding about the dependence of the Mueller matrix on its microstructural properties was overcome by transforming 16 Mueller elements into sub-matrices with specific structural and physical properties using Lu–Chipman-based Mueller matrix polar decomposition method. The obtained properties such as retardance, diattenuation, and depolarization were used for investigating the composition and microstructural information. The approach presented in this work has the potential to understand the virology of the coronavirus at the structural level and, therefore, will be beneficial in developing effective detection strategies by exploiting their characteristic electromagnetic scattering signatures.

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Section: Methodsmentioning

confidence: 99%

Stokes–Mueller polarization-based analysis of model SARS-CoV-2 virions

et al. 2023

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“…Fortunately, there always exists difference in polarization characteristics between the targets and the backgrounds. Moreover, polarized lights also have good anti-scattering effects [22][23][24][25]. Therefore, polarization computational ghost imaging provides additional information for contrast-enhanced target recognition in traditional ghost imaging [26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

High-performance deep-learning based polarization computational ghost imaging with random patterns and orthonormalization

Fan

et al. 2023

Phys. Scr.

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Polarization computational ghost imaging (PCGI) often requires a large number of samples to reconstruct the targets, which can be optimized by reducing sampling rates with the aids of deep-learning technology. In this paper, the random patterns and successive orthonormalization instead of common Hadamard patterns, has been introduced into the deep-learning based PCGI system to recover high-quality images at lower sampling rates. Firstly, we use a polarized light to illuminate the target with random patterns for sampling. Then we can obtain a vector of bucket detector values containing the reflective information of the target. Secondly, we orthonormalize the vector according to the random patterns. Subsequently, the orthonormalized data can be input into the Improved U-net (IU-net) for reconstructing the targets. We demonstrate that higher-quality image of the testing sample can be obtained at a lower sampling rate of 1.5%, and superior-generalization ability for the untrained complex targets can be also achieved at a lower sampling rate of 6%. Meanwhile, we have also investigated the generalization ability of the system for the untrained targets with different materials that have different depolarization properties, and the system still demonstrates superior performances. The proposed method may pave a way towards the real applications of the PCGI.

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Computational ghost imaging with key-patterns for image encryption

Guo

et al. 2023

Optics Communications

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Depolarization Characteristics of Different Reflective Interfaces Indicated by Indices of Polarimetric Purity (IPPs)

Cited by 15 publications

References 50 publications

Stokes–Mueller polarization-based analysis of model SARS-CoV-2 virions

Stokes–Mueller polarization-based analysis of model SARS-CoV-2 virions

High-performance deep-learning based polarization computational ghost imaging with random patterns and orthonormalization

Computational ghost imaging with key-patterns for image encryption

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