Ghost imaging LiDAR via sparsity constraints using push-broom scanning

Chenglong Wang; Chenyu Hu; Enrong Li; Jianrong Wu; Shensheng Han; Shuang Ma; Wenlin Gong; Xia Shen; Zhentao Liu; Zhishen Tong

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Ghost imaging LiDAR via sparsity constraints using push-broom scanning

Shuang Ma, Zhentao Liu, Chenglong Wang, Chenyu Hu, Enrong Li, Wenlin Gong, Zhishen Tong, Jianrong Wu

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Xia Shen, Shensheng Han

Image and Video Processing · Submitted 1 Apr 2019

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Numerical simulations and experiments have demonstrated its efficiency.

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arXiv ID1904.01010 (version 1)

Pith IDNAX2ONSF, Pith's permanent record of this paper and its review

CitationChenglong Wang, Chenyu Hu, Enrong Li, Jianrong Wu, Shensheng Han, Shuang Ma, Wenlin Gong, Xia Shen, Zhentao Liu, Zhishen Tong. "Ghost imaging LiDAR via sparsity constraints using push-broom scanning." arXiv:1904.01010 (2019). https://pith.science/paper/NAX2ONSF

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,539 input tokens.

What the abstract itself states, as probabilities: claims first 0.05 · states limitation 0.08 · human participants 0.02 · controlled comparison 0.65 · randomized assignment 0.01 · states quantitative result 0.04 · compares with prior results 0.89 · mentions code or data availability 0.02.

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Ghost imaging LiDAR via sparsity constraints using push-broom scanning is proposed. It can image the stationary target scene continuously along the scanning direction by taking advantage of the relative movement between the platform and the target scene. Compared to conventional ghost imaging LiDAR that requires multiple speckle patterns staring the target, ghost imaging LiDAR via sparsity constraints using push-broom scanning not only simplifies the imaging system, but also reduces the sampling number. Numerical simulations and experiments have demonstrated its efficiency.

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#	sentence	role	the authors' own work	states the main conclusion	strength
s0	Ghost imaging LiDAR via sparsity constraints using push-broom scanning is proposed.	contribution 1.00	0.75	0.12	asserted 0.99
s1	It can image the stationary target scene continuously along the scanning direction by taking advantage of the relative movement between the platform and the target scene.	method 0.87	0.43	0.10	asserted 0.87
s2	Compared to conventional ghost imaging LiDAR that requires multiple speckle patterns staring the target, ghost imaging LiDAR via sparsity constraints using push-broom scanning not only simplifies the imaging system, but also reduces the sampling number.	contribution 0.88	0.41	0.31	asserted 1.00
s3	Numerical simulations and experiments have demonstrated its efficiency.	result 0.98	0.93	0.40	asserted 1.00

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Original abstract

Ghost imaging LiDAR via sparsity constraints using push-broom scanning is proposed. It can image the stationary target scene continuously along the scanning direction by taking advantage of the relative movement between the platform and the target scene. Compared to conventional ghost imaging LiDAR that requires multiple speckle patterns staring the target, ghost imaging LiDAR via sparsity constraints using push-broom scanning not only simplifies the imaging system, but also reduces the sampling number. Numerical simulations and experiments have demonstrated its efficiency.

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Unlike the push-broom scanning method [ref] , we will not combine all the linear equations together to form super large augmented equations $C=AO$, where $A=diag{A_1,A_2,⋯,A_t}$, $Ω=[ω_1,ω_2,⋯,ω_t]^T$, $C=[c_1,c_2,⋯,c_t]^T$, diag denotes the diagonal matrix, $T$ represents the transpose symbol.

Three-dimensional imaging with single-frame jigsaw-puzzle-reorganized sinusoidal fringe using multi-pixel axial flat brush scanning · Section · 0.88

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