Single quantity estimation method for single photon lidar dehazing imaging

Guo, Shihang; Wei, Lu; Sun, Jianfeng; Liu, Di; Zhou, Xin; Jiang, Peng

doi:10.37188/ope.2020.0549

Cited by 7 publications

(2 citation statements)

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“…To mitigate limitations in imaging through or within smoky scattering media, numerous researchers have conducted studies on anti-smoke interference imaging from the spatial distribution [6][7][8] , polarization properties [9][10][11] , and temporal distribution [12,13] of scattered photons. Currently, several studies have investigated three-dimensional single-photon imaging through different types of atmospheric obscurants, including defogging based on optical system design [14][15][16] , photon-efficient imaging algorithms [17][18][19] , and establishment of smoke scattering models [20][21][22][23][24][25][26][27][28][29] . However, an increase in smoke attenuation coefficient can lead to an increase in the number of scattered photons, causing a mixture of target reflected photons and scattered photons, which reduces the signal-to-noise ratio of the target.…”

Section: Introductionmentioning

confidence: 99%

Edge-guided image estimation for array Gm-APD Lidar in smoky environment using multi-scale depth images

Zhang,

Li,

Sun

et al. 2023

6th Optics Young Scientist Summit (OYSS 2023)

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Limited statistical frame number and strong backscatter interference from smoke result in a photon-starved regime, severely limiting the depth imaging capability of array Gm-APD lidar in smoky environment. Here, we propose a depth image estimation algorithm that can significantly improve the integrity of targets in dense smoke environments when signal photons are starved. At the signal level, the algorithm improves the accuracy of extracting signal photons by constructing multi-scale superpixels. At the image level, using edge information of depth images at different scales to guide and fill the original scale depth image achieves efficient noise reduction and improves target integrity. It has been successfully demonstrated under different attenuation lengths and statistical frame numbers. Compared with other state-of-the-art methods, the proposed algorithm has maximum target recovery and structural similarity, especially for the attenuation length (AL) is 3.6 and statistical frame number is 1500 (imaging time is 75ms). This study is of great significance for the fast depth imaging of dynamic targets by array Gm-APD lidar in dense smoke environments.

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Section: Introductionmentioning

confidence: 99%

Edge-guided image estimation for array Gm-APD Lidar in smoky environment using multi-scale depth images

Zhang,

Li,

Sun

et al. 2023

6th Optics Young Scientist Summit (OYSS 2023)

Self Cite

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“…However, the smoke distribution model (Gamma) proposed by Satat has achieved good defogging imaging for targets in indoor smoke environment [18][19][20] . The model considers that the smoke echo photons and target echo photons satisfy Gamma distribution and Gaussian distribution respectively.…”

Section: Introductionmentioning

confidence: 99%

Estimation of smoke echo signal using single-photon lidar

Zhang

Sun

et al. 2022

Thirteenth International Conference on Information Optics and Photonics (CIOP 2022)

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The non-uniform distribution of smoke and laser spot seriously limits the imaging ability of single-photon lidar through smoke. To this end, based on the collision theory between photons and smoke particles, this paper establishes the time-domain distribution model of scattered photons (Gamma), which considers the lidar system parameters and the characteristics of smoke particles. The shape parameter and inverse scale parameter are defined as the maximum scattering number K and the average scattering number β, respectively. The indoor test effectively illustrates the estimation ability of the model for smoke. The parameter estimation results show that the average scattering number β and the maximum scattering number K increase linearly with the increase of attenuation coefficient. This study is of great significance for the suppression of smoke backscattering and is expected to improve the weather adaptability of single-photon lidar.

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Three-dimensional imaging of ships in the foggy environment using a single-photon detector array

Zhang

Sun

et al. 2023

Optik

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Single quantity estimation method for single photon lidar dehazing imaging

Cited by 7 publications

References 0 publications

Edge-guided image estimation for array Gm-APD Lidar in smoky environment using multi-scale depth images

Edge-guided image estimation for array Gm-APD Lidar in smoky environment using multi-scale depth images

Estimation of smoke echo signal using single-photon lidar

Three-dimensional imaging of ships in the foggy environment using a single-photon detector array

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