基于中频域维纳滤波的非视域成像算法研究  

Non-line-of-sight imaging algorithm based on Wiener filtering of mid-frequency

作　　者：唐佳瑶 罗一涵[1,2,3] 谢宗良 夏诗烨[1,2] 刘雅卿 徐少雄 马浩统 曹雷[1,2,3] Tang Jia-Yao;Luo Yi-Han;Xie Zong-Liang;Xia Shi-Ye;Liu Ya-Qing;Xu Shao-Xiong;Ma Hao-Tong;Cao Lei(Key Laboratory of Optical Engineering,Chinese Academy of Sciences,Chengdu 610209,China;Institute of Optics and Electronics,Chinese Academy of Sciences,Chengdu 610209,China;University of Chinese Academy of Sciences,Beijing 100049,China;School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院光束控制重点实验室,成都610209 [2]中国科学院光电技术研究所,成都610209 [3]中国科学院大学,北京100049 [4]中国科学院大学电子电气与通信工程学院,北京100049

出　　处：《物理学报》2023年第1期186-195,共10页Acta Physica Sinica

基　　金：国家自然科学基金(批准号:62271468);中国科学院青年创新促进会(批准号:2020372)资助的课题。

摘　　要：非视域成像是对探测器视线外被遮挡的物体进行光学成像的新兴技术,基于光锥变换反演法的非视域成像可以看作是一个反卷积的过程,传统维纳滤波反卷积方法是使用经验值或者反复尝试得到瞬态图像的功率谱密度噪信比(power spectral density noise-to-signal ratio,PSDNSR)进行维纳滤波反卷积,但非视域成像每个隐藏场景的PSDNSR都不同,先验估计难以适用.因此本文提出使用捕获瞬态图像的中频域信息来估计PSDNSR进行维纳滤波从而实现非视域成像.实验表明,基于中频域维纳滤波的非视域成像算法估计的PSDNSR能够落在一个重建效果较好的量级上.相比其他方法,本文算法能一步直接估计出PSDNSR,没有迭代运算,计算复杂度低,能够在保证重建效果的前提下提升重建效率.Non-line-of-sight(NLOS)imaging is an emerging technology for optically imaging the objects blocked beyond the detector’s line of sight.The NLOS imaging based on light-cone transform and inverted method can be regarded as a deconvolution process.The traditional Wiener filtering deconvolution method uses the empirical values or the repeated attempts to obtain the power spectral density noise-to-signal ratio(PSDNSR)of the transient image:each hidden scene has a different PSDNSR for NLOS imaging,so the prior estimation is not appropriate and repeated attempts make it difficult to quickly find the optimal value.Therefore,in this work proposed is a method of estimating the PSDNSR by using the mid-frequency information of captured transient images for Wiener filtering to achieve NLOS imaging.In this method,the turning points between the mid-frequency domain and the high-frequency domain of the transient image amplitude spectrum are determined,and then the PSDNSR value is solved by analyzing the characteristics and relationship among the noise power spectra at the low,middle and high frequency.Experiments show that the PSDNSR estimated by NLOS imaging algorithm based on Wiener filtering of mid-frequency domain has a better reconstruction effect.Compared with other methods,the algorithm in this work can directly estimate PSDNSR in one step,without iterative operations,and the computational complexity is low,thereby simplifying the parameter adjustment steps of the Wiener filtering deconvolution NLOS imaging algorithm based on light-cone transform.Therefore the reconstruction efficiency can be improved on the premise of ensuring the reconstruction effect.

关 键 词：非视域成像 光锥变换 反卷积 中频域 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]