Research On Correlated Imaging Algorithm And Target Feature Extraction Under Environmental Interference

Correlated Imaging,also known as ghost imaging(GI),is an indirect imaging technique that uses the second-order or even higher order correlation of the optical field to reconstruct an object.It is different from traditional optical imaging techniques which use a plane-array detector to directly obtain the image of an object that GI uses a certain algorithm to calculate the image.In ghost imaging schemes,the illumination is first divided into signal light and reference light.The signal light illuminates an object and is detected by a single-pixel detector without spatial resolution;the reference light is freely propagated and detected by a plane-array detector.Neither of the light alone can shape an image of the object;only by calculating the second-order correlation of the signal light and reference light the object can be reconstructed.Compared with traditional imaging techniques,there are many advantages in GI,such as suitability of working in complex environments,low complexity,the separation of detection and suitability of low light environment.Therefore,GI has attracted increasing attention and opened new avenues for medical imaging,military reconnaissance and surveillance,machine vision,remote sensing imaging and so on.However,there are some shortcomings in current research on the GI,such as the slow sampling speed,the long computation time,the poor image quality and the lagging applied research.Especially in the field of military reconnaissance and surveillance,the research on the influence of complex battlefield environment and how to improve the imaging quality of GI is limited.In order to promote the practicality of ghost imaging,the algorithm and target feature extraction of GI under environmental interference are deeply studied in this dissertation.The main contributions of the research work are as follows.1.A mathematical model of compressive sensing ghost imaging is built.Based on the analysis of thermal light ghost imaging,the physical model of ghost imaging is built.In this model,the statistical characteristics of thermal light are calculated based on the Goodman speckle theory,the ghost imaging formula is derived based on the classical diffraction theory and the object is reconstructed by the compressive sensing algorithm.In order to verify the effectiveness of this model,we started numerical simulations,in which a digital micro-mirror device was used to modulate the illuminations and some usual compressive sensing algorithms were compared.2.The influence of environmental interference on ghost imaging is studied.According to the analysis of actual applications and imaging performance of ghost imaging under environmental interference,the interference factors including diffraction,atmospheric turbulence and platform vibration are summarized,and the effects of these factors on ghost imaging are quantitatively calculated.In simulations,we have simulated the sampling process under environmental interference and analyzed the performance of ghost imaging.It is found that the environmental interference makes the sampling data less effective,which leads to the sharp decline in the reconstruction accuracy of existing algorithms.3.A feedback reconstruction algorithm based on neighborhood similarity is proposed.In order to improve the imaging quality of ghost imaging under environmental interference,a priori information,Neighbor similarity(NS),is chosen as a feedback indicator and applied in reconstruction algorithm to improve imaging performance.The results of simulations and experiments showed that the proposed algorithm is superior to existing reconstruction algorithms under environmental interference.4.The edge extraction scheme based on ghost imaging is researched.We first proposed the edge extraction mode of "first imaging and then extraction".In this mode,we introduced and analyzed the performance of gradient ghost imaging(GGI)based on different gradient extraction operators.Then the Multidirectional gradient ghost imaging(MGGI)based on Kirsch operator is first proposed.The results of simulations and experiments showed that MGGI has higher edge extraction accuracy and better anti-noise performance.5.The corner extraction scheme based on ghost imaging is researched.On the basis of summarizing four fusion modes of corner detection method and correlation imaging system,a corner detection scheme based on gradient ghost imaging system is designed,in which the curvature scale space(CSS)corner detection algorithm and the gradient ghost imaging based on Canny operator(GGI-Canny)are combined.The results of simulations and experiments showed that our method can accurately and efficiently extract the corner information of an object under environmental interference,which promotes the practical development of ghost imaging.