Spatial domain sparse reconstruction algorithm of sheared beam imaging

Chen, Minglai; Liu, Hui; Zhang, Yu; Luo, Xiang-Qian; Ma, Caiwen; Yue, Zelin; Zhao, Jing

doi:10.7498/aps.71.20220494

Cited by 3 publications

(7 citation statements)

References 22 publications

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“…The four-beam sparse sampling imaging system emits one less laser beam than the five-beam sparse sampling imaging system, 15 and the number of detector elements is the same for both systems. The hardware cost of the four-beam sparse sampling imaging system is less than that of the five-beam sparse sampling imaging system.…”

Section: Comparison With Other Methodsmentioning

confidence: 99%

“…Then, a detector array is used to receive the echo signal scattered from the target, which realize the encoding of target spatial frequency in the time domain 7 – 9 So far, researchers have studied the effect of atmospheric turbulence effect on imaging, 10 – 12 phase difference detection method, 13 image reconstruction algorithm, 14 , 15 image quality influencing factors and improvement methods, 16 , 17 and experimental verification 18 …”

Section: Introductionmentioning

confidence: 99%

“…Recently, Ref. 15 proposed a five-beam sparse sampling imaging method. The imaging system emitted five coherent laser beams simultaneously to illuminate the target to realize the sparseness of detector array.…”

Section: Introductionmentioning

confidence: 99%

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Four-beam sparse phase retrieval algorithm for sheared-beam imaging

Chen

Zhang

et al. 2023

Opt. Eng.

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.Sheared-beam imaging (SBI) is an effective way of imaging through turbulent medium, such as atmosphere or scattering liquid. Traditionally, the imaging is based on the laser transmitter array consisting of three beams or five beams for coherent illumination to the remote object. Compared with the existing SBI methods, the four-beam sparse sampling imaging method has been proposed, which may have more advantages; it not only sparses the detector elements but also reduces the number of emitted beams. However, the traditional phase retrieval algorithms are not suitable for the four-beam sparse sampling imaging. We propose a four-beam sparse phase retrieval (F-BSPR) algorithm, which uses the phase differences from both horizontal and vertical components and the phase differences from other components when the phase is retrieving. The proposed phase retrieval algorithm can better connect the phase difference and improve the accuracy of the phase retrieval. Furthermore, the imaging quality is improved. Simulation and experimental results show that the proposed algorithm is effective and feasible when the number of detector elements is sparse by 50%. Compared to the traditional four-beam phase retrieval method, the proposed F-BSPR method has better imaging quality and robustness.

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Section: Comparison With Other Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Four-beam sparse phase retrieval algorithm for sheared-beam imaging

Chen

Zhang

et al. 2023

Opt. Eng.

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“…The coherent laser beams in a two-dimensional array are emitted to illumate the target, and the echo signals are received via detector array which has been sparse. Assuming that the number of coherent lasers is MN  , the transverse and longitudinal emission shear length is , The optical field expression at any point ( ', ') xy on the surface of the target is [15] :…”

Section: The Principle Of Sparse Sampling In Two-dimensional Spatial ...mentioning

confidence: 99%

“…The literature [15] proposed a one dimensional sparse sampling imaging method for the SBI system, where five laser beams are emitted at once and the number of detector elements in the detector array can be sparse as much as half of the traditional three-beam imaging system. This paper proposes a two-dimensional sparse sampling imaging method, which extends the one-dimensional sparsity of the detector array to two-dimensional sparsity, and further reduces the number of detector elements.…”

Section: Introductionmentioning

confidence: 99%

A sparse sampling method in the two-dimensional spatial domain for sheared-beam imaging receiving system

Chen

Luo

et al. 2023

SPIE-CLP Conference on Advanced Photonics 2022

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In the imaging of low-orbit moving objects, the number of detector elements in the traditional sheared-beam imaging (SBI) system is too great, which seriously restrict the application of SBI. In this paper, the detector array is sparse in two dimensions. We propose a two-dimensional sparse sampling imaging method, which emits a two-dimensional coherent laser array, carries more spectral information of the target at a time and receives speckle echo signals by a twodimensional sparse detector array for computational imaging. This method can reduce the number of detector elements many times. Firstly, the principle of two-dimensional sparse sampling with SBI detector array is deduced theoretically. Secondly, a two-dimensional spatial sparse reconstruction algorithm is investigated. The target amplitude product and phase difference carried by each detector array element is estimated using discrete Fourier transform, then the target amplitude product and phase difference of all detector array elements are matched respectively to form a complete target amplitude product surface and phase difference surface. The formulas of phase recovery and amplitude demodulation are derived. Finally, the validity and feasibility of the proposed method are verified by simulation. Compared with the traditional three-beam method, when the number of lasers in emission array is M×N, the number of detector elements is reduced to 1/(M-1)/(N-1) of the original without loss of imaging resolution.

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Fast sampling based image reconstruction algorithm for sheared-beam imaging

Chen,

Ma,

Liu

et al. 2024

Acta Phys. Sin.

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Sheared-beam imaging (SBI) is an unconventional ground-based optical imaging technique. It breaks through the traditional optical imaging concept by illuminating the target with three coherent laser beams which are laterally displaced at the transmit plane, and reconstructs the target image from echo signals. However, the echo data sampling of the imaging system is still not fast enough to reconstruct the high resolution and clear image of the target when imaging the target with rapidly changing position and attitude. In order to solve this problem, this paper proposes an image reconstruction method based on five-beam fast sampling. An emitted beam array arranged in the cross shape with a central symmetrical structure is proposed, and the encoding and decoding method of the imaging system are changed. With a single exposure, the echo signals carry more spectrum information of the target, and the number of reconstructed images can be increased from 1 to 8, which quickly suppresses the speckle effect of the reconstructed image. Firstly, the principle of the imaging technique based on fast sampling is deduced. Then, an image reconstruction algorithm based on fast sampling is studied. Eight sets of phase difference and amplitude information of the target can be extracted from echo signals. The wavefront phases are solved by the least-squares method, and wavefront amplitude can be obtained by the algebraic operation of speckle amplitude. The target image is reconstructed by the inverse Fourier transform. The simulation results show that compared with the traditional three-beam image reconstruction method, the number of echo data sampling times required to obtain the same quality image is reduced from 20 times to 5 times, which greatly reduces the number of echo data sampling times and improves the echo data sampling rate.

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Spatial domain sparse reconstruction algorithm of sheared beam imaging

Cited by 3 publications

References 22 publications

Four-beam sparse phase retrieval algorithm for sheared-beam imaging

Four-beam sparse phase retrieval algorithm for sheared-beam imaging

A sparse sampling method in the two-dimensional spatial domain for sheared-beam imaging receiving system

Fast sampling based image reconstruction algorithm for sheared-beam imaging

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