Experimental investigation of ghost imaging of reflective objects with different surface roughness

Nan, Suqin; Bai, Yanfeng; Shi, Xiaohui; Shen, Qian; Qu, Lijie; Li, Hengxing; Fu, Xiquan

doi:10.1364/prj.5.000372

Cited by 20 publications

(13 citation statements)

References 30 publications

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“…Experiments are designed to verify the above analysis of the performance of binary sampling GI. For the conventional GI setup [27,28], as shown in Fig. 3.…”

Section: Performance Analysismentioning

confidence: 99%

Ghost Imaging with the Optimal Binary Sampling

Yang,

Wu,

Luo

et al. 2020

Preprint

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To extract the maximum information about the object from a series of binary samples in ghost imaging applications, we propose and demonstrate a framework for optimizing the performance of ghost imaging with binary sampling to approach the results without binarization. The method is based on maximizing the information content of the signal arm detection, by formulating and solving the appropriate parameter estimation problem -finding the binarization threshold that would yield the reconstructed image with optimal Fisher information properties. Applying the 1-bit quantized Poisson statistics to a ghost-imaging model with pseudo-thermal light, we derive the fundamental limit, i.e., the Cramér-Rao lower bound, as the benchmark for the evaluation of the accuracy of the estimator. Our theoertical model and experimental results suggest that, with the optimal binarization threshold, coincident with the statistical mean of all bucket samples, and large number of measurements, the performance of binary sampling GI can approach that of the ordinary one without binarization.

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“…Experiments are designed to verify the above analysis of the performance of binary sampling GI. For the conventional GI setup [27,28], as shown in Fig. 3.…”

Section: Performance Analysismentioning

confidence: 99%

Ghost Imaging with the Optimal Binary Sampling

Yang,

Wu,

Luo

et al. 2020

Preprint

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“…Cheng and Han studied a particular aspect of coincidence imaging with incoherent source by using classical statistical optics [7]. After that, theoretical and experimental CI schemes exploiting the correlation of two classical beams obtained by splitting incoherent thermal source were proposed [9][10][11][12][13][14][15][16][17]. Furthermore, many relevant results including high-order [18,19], computational [20,21], differential [22], and compressive sensing [23,24] were also reported.…”

Section: Introductionmentioning

confidence: 99%

Research on Multipath Correlated Imaging with the Grayscale Target in Endoscopic Applications

et al. 2021

Self Cite

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The application of correlated imaging in endoscope, one of the research hotspots, may lead to multipath effect in the closed endoscopic environment. The model of multipath correlated imaging with a grayscale object is given, where the mismatch ratio and the reflection ratio are two key factors affecting imaging quality. The theoretical and experimental results show that multipath effect has an influence on the grayscale distribution and imaging quality of the reconstructed image, and the effect of the mismatch ratio is stronger than that of the reflection ratio. The conditions that the disturbance from multipath effect can be ignored in endoscopic applications are given.

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“…Recently, researchers have explored the effects of the roughness on the GI, and experimental results demonstrated that the signal-to-noise ratio (SNR) of GI decreases along with the increase of surface roughness. 17,18 As everyone knows, when the difference of the reflectivity or transmittance between objects and background is not apparent, it is difficult for conventional imaging to distinguish them, especially underwater. When the light transferring in the water, the energy will be attenuated or absorbed due to underwater dissolved organic matter and suspended particles, but some proposed method can produce reliable and promising results.…”

Section: Introductionmentioning

confidence: 99%

Ghost imaging enhancement for detections of the low-transmittance objects

Zhang

et al. 2020

International Journal of Advanced Robotic Systems

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The underwater environment is extremely complex and variable, which makes it difficult for underwater robots detecting or recognizing surroundings using images acquired with cameras. Ghost imaging as a new imaging technique has attracted much attention due to its special physical properties and potential for imaging of objects in optically harsh or noisy environments. In this work, we experimentally study three categories of image reconstruction methods of ghost imaging for objects of different transmittance. For high-transmittance objects, the differential ghost imaging is more efficient than traditional ghost imaging. However, for low-transmittance objects, the reconstructed images using traditional ghost imaging and differential ghost imaging algorithms are both exceedingly blurred and cannot be improved by increasing the number of measurements. A compressive sensing method named augmented Lagrangian and alternating direction algorithm (TVAL3) is proposed to reduce the background noise imposed by the low-transmittance. Experimental results show that compressive ghost imaging can dramatically subtract the background noise and enhance the contrast of the image. The relationship between the quality of the reconstructed image and the complexity of object itself is also discussed.

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Experimental investigation of ghost imaging of reflective objects with different surface roughness

Cited by 20 publications

References 30 publications

Ghost Imaging with the Optimal Binary Sampling

Ghost Imaging with the Optimal Binary Sampling

Research on Multipath Correlated Imaging with the Grayscale Target in Endoscopic Applications

Ghost imaging enhancement for detections of the low-transmittance objects

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