Research On The Image Efficiency And The Optimization Methods Of Ghost Imaging System

As an indirect modality of imaging,correlation imaging,which is also been called as ghost imaging(GI)is totally different from traditional imaging method.The special scheme of GI brought it many novel features such as single-pixel detection,lensless imaging,high-order measurements,and the potential to be superior to the classical optical imaging,in the aspects such as turbulence resistance,high resolution.However,one of the key problems in the application of ghost imaging is that compared with traditional imaging,GI requires more resources during one imaging procedure,including time consumption,such as data acquisition and storage,image reconstruction;and hardware consumption,such as the design and setting up of the light source,speckle,detector.The problem,which limits the application of GI,is mainly caused by the requirement of multiple sampling.Therefore,in this paper we defined the concept of imaging efficiency in GI and proposed two kinds of methods to improve imaging efficiency.The main contents include:1.Retrieve more information of object in reconstructed images with fewer space and time source:The details can be divided into two aspects:1)Shorten the number of sampling,and retrieve the same or even higher amount of information with fewer samples in reconstructed images.In this part,we proposed a algorithm,in which we calculated the expected intensity of pixels in object area and non-object area with a little data acquired based on the difference between the intensity of pixels in object area and non-object area,then we modified subsequent data during sampling accordingly.Simulation and experimental results show that the research can reduce the necessary number of samples by about 50%.2)Reduce the size of sampling ROI in collected data and obtain the information matching the original data with fewer pixels.In this part,we propose a method in which main information of the original light field can retained with a smaller light field.The research is based on that pixels of different intensity in the reference arm light field have different contributions to the reconstructed image.Simulation and experimental results show that the image reconstruction can still be achieved when the light field is compressed to 1/1024 compared with the initial light field.2.Retrieve more information based on existing hardware architecture:The details are as follows:1)To solve the problem of periodic structural noise caused by improper application of synthetic aperture.In this part,we further optimize the existing CLEAN algorithm referring to eliminate the spatial periodic structure noise and realize the complement of the missing part of the object in the reconstructed image.2)To solve the problem of motion blur in reconstructed images caused by low power light source and inproper exposure time of detectors.In this part,we introduced Hessian matrix to adjust the reference arm light field,and use the change of its pixel gray gradient to carry out reconstruction procedure instead of its intensity information.3)To solve the problem of low resolution caused by improper speckle field modulation.In this part,we added a random mask to the dualarm data to break the correlation between adjacent pixels and improve the imaging resolution.The simulation and experimental results show that the above three studies can reduce the structural noise while completing the incomplete part of the target object in the reconstructed image,reduce the influence of motion blur on the reconstructed image,and improve the resolution of the reconstructed image,which help solve the problems caused by hardware in the form of algorithm.Through the above researches,we successfully reduced the time and space resource requirements of associated imaging,solved various problems caused by hardware architecture in the form of algorithm and increased the information of the object in reconstructed images.Thus we successfully realized the improvement of imaging efficiency of GI system.