已知窗口形状的被动非视域成像  

Passive Non-line-of-sight imaging with known window shape

作　　者：孙佳科 王维东[1] SUN Jiake;WANG Weidong(Zhejiang Provincial Key Laboratory of Information Processing and Communication Networks,College of Information Science and Electronic Engineering,Zhejiang University,Hangzhou310027,China)

机构地区：[1]浙江大学信息与电子工程学院浙江省信息处理与通信网络重点实验室,浙江杭州310027

出　　处：《光学技术》2025年第2期129-135,共7页Optical Technique

摘　　要：非视域成像是对视线外场景进行成像,可以分为主动非视域成像和被动非视域成像。主动非视域成像使用主动光源及探测器对非视域场景进行成像。被动非视域成像则依赖于场景发出的光或反射光,利用物体、墙角和窗口对非视域场景进行成像。现有利用窗口进行被动非视域成像的方法只针对矩形窗口,需要已知窗口形状、尺度和位置。然而现实生活中窗口形状各异,且很难得到其精确尺度和位置。为此,提出一种已知窗口形状的被动非视域成像方法。首先,分析非视域场景通过窗口照射到漫反射面上的漫反射图像形成原理,构建模型;其次,在窗口形状已知的情况下,选取一系列不同尺度的窗口构建可视矩阵,并用L0梯度稀疏约束进行求解,选择最小均方误差对应的窗口尺度作为最终窗口尺度;最后,细化窗口,并对场景和窗口联合优化得到最终重建场景。实验结果表明针对不同形状窗口,该方法可以在只知道窗口形状的情况下重建非视域场景实现非视域成像,与其他方法相比,恢复的成像结果在PSNR和SSIM上平均提高0.461dB和0.0361。Non-Line-of-Sight imaging is the imaging of scenes outside the line of sight,which can be divided into active Non-Line-of-Sight imaging and passive Non-Line-of-Sight imaging.Active Non-Line-of-Sight imaging uses active light sources and detectors to image Non-Line-of-Sight scenes.Passive Non-Line-of-Sight imaging relies on the light emitted or reflected from the scene,using objects,corners and windows to image the Non-Line-of-Sight scene.The existing methods of passive Non-Line-of-Sight imaging using windows are only for rectangular windows,and need to know the shape,scale and position of the window.However,in real life,windows have different shapes,and it is difficult to know their specific scale and position.Therefore,a passive Non-Line-of-Sight imaging method with known window shapes is proposed.Firstly,analyze the formation principle of the diffuse reflection image of the Non-Line-of-Sight scene illuminated through the window onto the diffuse reflection surface,and construct the model.Secondly,a series of windows with different scales are selected based on the known window shape to construct the visual matrix,and the L0 gradient sparse constraint is used to solve it.Select the window scale corresponding to the minimum mean square error as the final window scale.Finally,refine the window,and optimize the scene and window jointly to obtain the final reconstructed scene.Experimental results show that for windows with different shapes,the proposed method can reconstruct Non-Line-of-Sight scenes when only the shapes of windows known and realize the Non-Line-of-Sight imaging.Compared with other methods,the average PSNR of the reconstructed imaging results is increased by 0.461dB,and the average SSIM is increased by 0.0361.

关 键 词：被动非视域成像 漫反射 可视矩阵 L0梯度稀疏约束 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] O439[自动化与计算机技术—计算机科学与技术]