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基于漫反射的被动非视域成像

吴翠翠 王维东

计算机工程2024,Vol.50Issue(5):26-32,7.
计算机工程2024,Vol.50Issue(5):26-32,7.DOI:10.19678/j.issn.1000-3428.0067904

基于漫反射的被动非视域成像

Passive Non-Line-of-Sight Imaging Based on Diffuse Reflection

吴翠翠 1王维东1

作者信息

  • 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 310013
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摘要

Abstract

Non-Line-of-Sight(NLOS)imaging,which combines imaging and computational reconstruction,describes the reconstruction of hidden scenes in a medium by capturing scattered or reflected information without directly imaging the scene.NLOS imaging is still in the early stages of its development,and systematic research methods for scene modeling and target information reconstruction are lacking.To address these issues,an NLOS imaging method for unobstructed and non-self-luminous scenes is proposed.Based on optical radiation theory,the relationship between the imaging of diffuse reflection surfaces in the scene and the shape of hidden objects is analyzed to determine the NLOS imaging model and reconstruction targets.A Diffuse reflection full-Shadow passive NLOS(DS-NLOS)dataset that resembles physical reality is generated by combining a rendering software with the Motion Picture Experts Group 7(MPEG7)dataset.A passive NLOS Reconstruction network model(Re-NLOS)is constructed using a Visual Transformer(ViT)structure in combination with a Generative Adversarial Network(GAN)to extract global features from captured diffuse reflection surface images and recover the shape of hidden objects.Experimental results on the DS-NLOS dataset demonstrate that this method can recover the shape information of hidden objects from diffusely reflected surfaces.In comparison with the diffuse reflection full-shadow images,the average Peak Signal-to-Noise Ratio(PSNR)for 20 object categories in the present test set is increased by 5.85 dB,and the average Structural SIMilarity(SSIM)is increased by 0.038 1.This method also demonstrates restore capabilities in real indoor scenes.

关键词

被动非视域成像/漫反射/全影图像/生成式对抗网络/亮度传输

Key words

passive Non-Line-of-Sight(NLOS)imaging/diffuse reflection/full-shadow image/Generative Adversarial Network(GAN)/brightness transfer

分类

信息技术与安全科学

引用本文复制引用

吴翠翠,王维东..基于漫反射的被动非视域成像[J].计算机工程,2024,50(5):26-32,7.

计算机工程

OA北大核心CSTPCD

1000-3428

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