Research On Ghost Imaging In Frequency Domain With High Signal-to-Noise Ratio

Ghost imaging(GI),also known as correlation imaging,is a new imaging technique based on correlation measurement of light field intensity.Ghost imaging uses a single-pixel detector as the detection device.Compared with traditional imaging technology,ghost imaging has the advantages of strong concealment,ability to penetrate obstacles,and anti-turbulence interference.However,ghost imaging technology also has some limitations,the most important of which are the imaging signal-to-noise ratio and imaging time of this technology.Ghost imaging has a low signal-to-noise ratio when the number of sampling measurements is small,and increasing the number of sampling will lead to too long detection time,which is not conducive to the application of ghost imaging technology.Aiming at the problem that the imaging quality of ghost imaging is not high enough,this paper first proposes a filtering-based method for improving the signal-to-noise ratio,and then based on the Fourier transform idea,proposes a frequency-domain ghost imaging technique,which can greatly improve the measurement time at the same time.The imaging signal-to-noise ratio is improved,and the light source linearization correction mechanism is introduced to improve the imaging signal-to-noise ratio of frequency domain ghost imaging in nonlinear light source systems.First,the signals of ambient light and sample signal light are simulated,and the frequencies of these two kinds of light are analyzed.A method is proposed to improve the image quality of ghost imaging,which can be immune to the influence of ambient light changes during the measurement.The method uses a digital high-pass filter to remove the interference of ambient light,improves the signal-to-noise ratio of the image,and significantly improves the image quality.Secondly,a Fourier frequency domain ghost imaging scheme based on orthogonal speckle is proposed.In this scheme,the random speckle pattern emitted by the light source is changed to a specially designed speckle pattern,so that the intensity signals of the light irradiated by different positions of the object to be measured have different changing frequencies,and the signals are orthogonal to each other;and an image restoration algorithm is designed.,which greatly improves the signal-to-noise ratio of the image and the operation speed.Simulation and experimental results show that,compared with traditional ghost imaging,Fourier frequency domain ghost imaging can obtain images with high signal-to-noise ratio of more than 10 d B under the same number of measurements.In addition,Fourier frequency domain ghost imaging has higher data processing speed.Finally,the method of data fitting and interpolation is used to realize the linearity correction of the light source,and the nonlinear relationship between the light intensity and time of the light source is corrected to linear,which is a method to optimize the image quality of Fourier frequency domain ghost imaging,compared with before correction,this method eliminates the harmonic artifacts caused by the nonlinearity of the light source,and further improves the image signal-to-noise ratio.The research results of this paper show that the use of digital filtering technology can reduce the influence of ghost imaging by ambient light interference and improve the signal-to-noise ratio of traditional ghost imaging.Compared with the traditional ghost imaging technology,the frequency domain ghost imaging technology based on Fourier transform greatly improves the imaging signal-to-noise ratio under the same sampling number.The light source linearization correction technology expands the range of light sources used in frequency domain ghost imaging and eliminates the problem of harmonic artifacts in images caused by nonlinear light sources.Combining the three,the technology proposed in this paper achieves the improvement of the imaging signal-to-noise ratio under the conditions of high-speed detection,ambient light variation and light source nonlinearity.