arXiv:2605.25757cs.CV2026-05International Conf…

实现450-1500nm全波段高光谱3D成像,突破传统传感器限制。

Broadband Hyperspectral 3D Imaging using Dispersed Structured Light

论文配图:Broadband Hyperspectral 3D Imaging using Dispersed Structured Light
图 1 · 摘自论文原文
  • 用单光谱仪结合双相机,扩展结构光至宽波段。
  • 平均光谱角误差0.13弧度,深度误差仅4.5毫米。
  • 可识别相似颜色材料、穿透遮挡层,看清钞票隐藏特征。

高光谱3D成像可捕获密集光谱信息与场景几何,但传统方法受限于窄光谱范围,通常仅覆盖可见光。本文提出宽带高光谱3D成像(BH3D)方法,将覆盖范围扩展至全可见-近红外及短波红外波段(450–1500 nm)。该波段覆盖对获取互补物理信息至关重要:可见光反映表面外观,而SWIR波段揭示次表层特性与材质组成。然而,实现此目标面临挑战——可见光硅基传感器与SWIR铟镓砷传感器间存在根本性设计矛盾,通常需复杂多光谱仪系统。为此,我们提出一种单光谱仪方案,采用可见光与SWIR双相机立体布局,重建稠密宽带高光谱反射率与精确3D几何结构。核心思路是将分散式结构光拓展至宽带范围,通过建模宽带分散结构光成像过程,联合估计高光谱反射率与深度。我们在多种真实场景中验证该方法,结果显示平均光谱角映射误差为0.13弧度,均方根误差为0.03,平均深度误差为4.5毫米。进一步实证其可识别色同质材料、透过不透明层成像、揭示钞票隐藏特征,并显现血管结构。

原文摘要 · Abstract (English)

Hyperspectral 3D imaging enables the capture of dense spectral information and scene geometry but has traditionally been confined to narrow spectral windows, typically the visible range. In this work, we introduce a broadband hyperspectral 3D imaging (BH3D) method to extend this capability across the full visible-near-infrared and short-wavelength infrared (SWIR) spectrum (450-1500 nm). This broad coverage is critical as it captures complementary physical cues: visible wavelengths reveal surface appearance, while SWIR bands provide insight into subsurface properties and material composition. However, realizing BH3D is challenging due to fundamental sensor constraints between visible-spectrum silicon and SWIR-spectrum InGaAs sensors, which necessitate complex multi-spectrograph designs. Here we propose a single-spectrograph BH3D system, using a stereo setup comprising visible and SWIR cameras, that reconstructs dense broadband hyperspectral reflectance together with accurate 3D geometry. Our key idea is to extend dispersed structured light to the broadband regime using a single spectrograph. We model the image formation of broadband dispersed structured light, and estimate hyperspectral reflectance and depth. We validate our approach on diverse real-world scenes, demonstrating accurate reconstruction with a mean spectral angle mapper of 0.13 rad, root mean square error of 0.03, and mean depth error of 4.5 mm. We further demonstrate identifying metameric materials, performing imaging through opaque layers, uncovering hidden features on banknotes, and revealing blood vessels.

高光谱成像3D重建红外成像结构光

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