摘要
针对传统鬼成像二阶关联运算中随机散斑图统计噪声的影响而无法对目标物体高质量成像的问题,提出基于梯度下降法的鬼成像重构方法。从矩阵的角度出发,结合梯度下降法对鬼成像中目标物体进行迭代重构。仿真实验结果表明:相比于传统鬼成像技术,该方法能有效地从原有实验数据中重建目标物体,并表现出良好的性能。
In order to solve the problem that the statistical noise of the random speckle patterns in the traditional second-order correlation operation of ghost imaging can not image the target with high quality,a reconstruction method of ghost imaging based on gradient descent method is proposed.From the perspective of matrix,combined with gradient descent method,the target object in ghost imaging is reconstructed iteratively.The simulation results show that compared with the traditional ghost imaging technology,this method can effectively reconstruct the target from the original experimental data,and shows good performance.
作者
郭辉
叶知秋
杨俊伟
GUO Hui;YE Zhiqiu;YANG Jun wei(College of Information Engineering,Fuyang Normal University,Fuyang Anhui 236037,China;Fuyang Emergency Management Bureau,Fuyang Anhui 236000,China)
出处
《阜阳师范大学学报（自然科学版）》
2021年第4期10-13,共4页
Journal of Fuyang Normal University:Natural Science
基金
安徽省高校优秀青年人才支持计划一般项目(gxyq2019175,gxyq2020102)
阜阳师范大学信息工程学院自然科学一般项目(2019FXGZK02)资助。
关键词
成像系统
鬼成像
梯度下降法
imaging system
ghost imaging
gradient descent method
