基于椭球模态分解的反投影多非视线目标重建
Reconstruction of multiple non-line-of-sight objects using back projection based on ellipsoid mode decomposition
摘要：
非视线成像因其广泛的应用而受到越来越多的关注，即使有超灵敏的相机或高时间分辨率的探测器，由于严重的混叠效应，现有的反投影方法仍然无法获得令人满意的多个隐藏目标的重建。在这里，开发了一种新的反投影方法来重建多个隐藏对象。我们的方法考虑将置信图中的所有椭球体分解为属于不同对象的几个簇（即椭球模式分解），然后分别通过滤波和阈值处理从椭球模式中重建对象。仿真和实验结果表明，该方法能有效消除混叠伪影的影响，在分离、定位和恢复多个隐藏目标方面具有潜在优势，为复杂非视距场景的重建奠定了良好的基础。
英文摘要：
Non-line-of-sight imaging has attracted more attentions for its wide applications.Even though ultrasensitive cameras or detectors with high time-resolution are available, current back-projection methods are still powerless to acquire a satisfying reconstruction of multiple hidden objects due to severe aliasing artifacts. Here, a novel back-projection method is developed to reconstruct multiple hidden objects. Our method considers decomposing all the ellipsoids in a confidence map into several clusters belonging to different objects (namely ellipsoid mode decomposition), and then reconstructing the objects individually from their ellipsoid modes by filtering and thresholding, respectively. Importantly, the simulated and experimental results demonstrate that this method can effectively eliminate the impacts of aliasing artifacts and exhibits potential advantages in separating, locating and recovering multiple hidden objects, which might be a good base for reconstructing complex non-line-ofsight scenes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
