scholarly journals Instant ghost imaging: improving robustness for ghost imaging subject to optical background noise

OSA Continuum ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 391 ◽  
Author(s):  
Zhe Yang ◽  
Wei-Xing Zhang ◽  
Ma-Chi Zhang ◽  
Dong Ruan ◽  
Jun-Lin Li
Keyword(s):  
Background Noise ◽  
Ghost Imaging ◽  
Optical Background

scholarly journals Ghost imaging enhancement for detections of the low-transmittance objects

2020 ◽  
Vol 17 (5) ◽  
pp. 172988142093233
Author(s):  
Ying Zhang ◽  
Wendong Li ◽  
Yonghe Yu ◽  
Ya Xiao ◽  
Dongyu Xu ◽  
...  
Keyword(s):  
Background Noise ◽  
Ghost Imaging ◽  
Noisy Environments ◽  
Underwater Robots ◽  
Underwater Environment ◽  
Reconstruction Methods ◽  
Alternating Direction ◽  
Imaging Algorithms ◽  
The Relationship

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.

scholarly journals Mitigation of the Influence of Optical Background Noise by Using Turbo-Coded DOOK

2015 ◽  
Vol 19 (6) ◽  
pp. 269-273 ◽  
Author(s):  
Sachin Rai ◽  
Yusuke Kozawa ◽  
Hiromasa Habuchi ◽  
Yuto Matsuda
Keyword(s):  
Background Noise ◽  
Optical Background

scholarly journals Computational Ghost Imaging Based on Light Source Formed by Coprime Array

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4508
Author(s):  
Yapeng Zhan ◽  
Jiying Liu ◽  
Zelong Wang ◽  
Qi Yu
Keyword(s):  
Background Noise ◽  
Spatial Light Modulator ◽  
Ghost Imaging ◽  
Light Modulator ◽  
Imaging Quality ◽  
Microwave Radar ◽  
Light Point ◽  
Uniform Array ◽  
Coprime Array ◽  
First Time

In computational ghost imaging, a spatial light modulator (SLM) can be used to modulate the light field. The relative locations and the number of light point pixels on an SLM affect the imaging quality. Usually, SLMs are two-dimensional arrays which are drawn uniformly or are randomly sparse. However, the patterns formed by a uniform array are periodic when the number of light point pixels is small, and the images formed by a random sparse array suffer from large background noise. In this paper, we introduce a coprime array based on the Eisenstein integer to optimize the light point pixel arrangement. A coprime array is widely used as a microwave radar receiving array, but less implemented in optics. This is the first time that a coprime array based on Eisenstein integer has been introduced in computational ghost imaging. A coprime array with this structure enhances the imaging quality when limited measurements are recorded, and it reduces background noise and avoids periodicity. All results are verified by numerical simulation.

scholarly journals The mechanism and suppression methods of optical background noise in phase-sensitive optical time domain reflectometry

2017 ◽  
Vol 66 (7) ◽  
pp. 070707
Author(s):  
Zhang Xu-Ping ◽  
Zhang Yi-Xin ◽  
Wang Feng ◽  
Shan Yuan-Yuan ◽  
Sun Zhen-Hong ◽  
...  
Keyword(s):  
Time Domain ◽  
Background Noise ◽  
Time Domain Reflectometry ◽  
Optical Time Domain Reflectometry ◽  
Optical Background ◽  
Phase Sensitive ◽  
Optical Time

Microdensitometer—computer correlation analysis of ultrastructural periodicity

1978 ◽  
Vol 36 (2) ◽  
pp. 32-33
Author(s):  
D.R. Ensor ◽  
C.G. Jensen ◽  
J.A. Fillery ◽  
R.J.K. Baker
Keyword(s):  
Correlation Analysis ◽  
Background Noise ◽  
Computer Control ◽  
Optical Diffraction ◽  
Screw Thread ◽  
Straight Line ◽  
Computer Storage ◽  
Correlation Process ◽  
Electron Microscope Image ◽  
Fixed Beam

Because periodicity is a major indicator of structural organisation numerous methods have been devised to demonstrate periodicity masked by background “noise” in the electron microscope image (e.g. photographic image reinforcement, Markham et al, 1964; optical diffraction techniques, Horne, 1977; McIntosh,1974). Computer correlation analysis of a densitometer tracing provides another means of minimising "noise". The correlation process uncovers periodic information by cancelling random elements. The technique is easily executed, the results are readily interpreted and the computer removes tedium, lends accuracy and assists in impartiality.A scanning densitometer was adapted to allow computer control of the scan and to give direct computer storage of the data. A photographic transparency of the image to be scanned is mounted on a stage coupled directly to an accurate screw thread driven by a stepping motor. The stage is moved so that the fixed beam of the densitometer (which is directed normal to the transparency) traces a straight line along the structure of interest in the image.

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