Research On Moving Target Compressive Imaging Based On Row Scanning Measurement

In this paper,a compressive sensing(CS)scanning imaging method,which has an advantage of high-throughput measurement,is employed to achieve visual moving target detecting in a very weak light condition.The blurring influence in the moving target row-scanning imaging is analyzed,and a motion measurement matrix is constructed to retrieve the target information by utilizing CS algorithm.Based on the theoretical analysis and numerical simulation,a set of experimental imaging device to verify the feasibility of this method is designed by introducing the digital micromirror device and the complementary compression measurement method.The experimental results show that a high quality moving object image can be obtained through this method.In this paper,the relationship between the image quality and velocity of moving objects and the anti-noise performance of the proposed imaging methods are analyzed qualitatively by introducing the image quality evaluation standard.An improved computational model and a study of variable linear motion imaging based on this model are proposed in this thesis.This deblurring method thus offers a very effective approach to promote the implementation of CS in real applications,and displays great applicable potential in scenarios such as remote sensing(especially airborne push to sweep)imaging,low light imaging and infrared imaging.