Experimental Research on Prebuilt Three-Dimensional Imaging Lidar

Xiaodong, 梅笑冬 Mei; Wenlin, 龚文林 Gong; Yi, 严毅 Yan; Shensheng, 韩申生 Han; Qing, 曹清 Cao

doi:10.3788/cjl201643.0710003

Cited by 10 publications

(3 citation statements)

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“…Subsequently, Bromberg 4 experimentally confirmed the feasibility of the CGI scheme and promoted the development of GI. Recently, GI has a wide range of applications in many fields, such as lidar imaging 5 – 7 , terahertz imaging 8 – 10 , X-ray imaging 11 – 14 , spectral imaging 15 – 18 , microscopic imaging 19 – 23 , etc. However, poor imaging quality and long measurement time limit the application and development of GI.…”

Section: Introductionmentioning

confidence: 99%

Fast high quality computational ghost imaging based on saliency variable sampling detection

Liu,

Hu,

et al. 2024

Sci Rep

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Fast computational ghost imaging with high quality and ultra-high-definition resolution reconstructed images has important application potential in target tracking, biological imaging and other fields. However, as far as we know, the resolution (pixels) of the reconstructed image is related to the number of measurements. And the limited resolution of reconstructed images at low measurement times hinders the application of computational ghost imaging. Therefore, in this work, a new computational ghost imaging method based on saliency variable sampling detection is proposed to achieve high-quality imaging at low measurement times. This method physically variable samples the salient features and realizes compressed detection of computational ghost imaging based on the salient periodic features of the bucket detection signal. Numerical simulation and experimental results show that the reconstructed image quality of our method is similar to the compressed sensing method at low measurement times. Even at 500 (sampling rate $$0.76\%$$ 0.76 % ) measurement times, the reconstructed image of the method still has the target features. Moreover, the $$2160\times 4096$$ 2160 × 4096 (4K) pixels ultra-high-definition resolution reconstructed images can be obtained at only a sampling rate of $$0.11\%$$ 0.11 % . This method has great potential value in real-time detection and tracking, biological imaging and other fields.

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Section: Introductionmentioning

confidence: 99%

Fast high quality computational ghost imaging based on saliency variable sampling detection

Liu,

Hu,

et al. 2024

Sci Rep

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“…The other is singlepixel camera (SPC), where the target is usually imaged onto a spatial modulation device and the modulated signals are received by a single-pixel detector [5,6] . Recently, some works have demonstrated that SPC has some obvious advantages in comparison with CGI and have attracted much more attention [7,8,[12][13][14] . For example, the structure of SPC usually satisfies the process of bucket detection in long-range imaging, and the reconstruction algorithm via compressive sensing is always valid [8,12] .…”

Section: Introductionmentioning

confidence: 99%

“…For example, the structure of SPC usually satisfies the process of bucket detection in long-range imaging, and the reconstruction algorithm via compressive sensing is always valid [8,12] . For another example, the detection range of CGI Lidar is limited by the damage threshold of the modulation device, whereas there is no need for the SPC to be considered because the reflection signal is usually weak [13] . In addition, the SPC is superior to CGI in the same light disturbance environment, and the structure's size of the SPC is usually smaller than that of CGI [14] .…”

Section: Introductionmentioning

confidence: 99%

Enhancing the ability of single-pixel imaging against the source’s energy fluctuation by complementary detection

Cai,

Gong

2024

中国光学快报

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The source's energy fluctuation has a great effect on the quality of single-pixel imaging (SPI). When the method of complementary detection is introduced into an SPI camera system and the echo signal is corrected with the summation of the light intensities recorded by two complementary detectors, we demonstrate, by both experiments and simulations, that complementary single-pixel imaging (CSPI) is robust to the source's energy fluctuation. The superiority of the CSPI structure is also discussed in comparison with previous SPI via signal monitoring.

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Distorted point spread function and image reconstruction for ghost imaging

Zhao

Gong

2021

Optics and Lasers in Engineering

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Experimental Research on Prebuilt Three-Dimensional Imaging Lidar

Cited by 10 publications

References 0 publications

Fast high quality computational ghost imaging based on saliency variable sampling detection

Fast high quality computational ghost imaging based on saliency variable sampling detection

Enhancing the ability of single-pixel imaging against the source’s energy fluctuation by complementary detection

Distorted point spread function and image reconstruction for ghost imaging

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