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Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales
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在大规模的3D重建中,基于全向传感器系统的纹理噪声校正.

Wenya Xie1, Xiaoping Hong1

  • 1The School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen 518055, China.

Sensors (Basel, Switzerland)
|January 11, 2024
PubMed
概括

这项研究提出了一个新的框架,用于减少使用全向传感器的大规模3D重建中的纹理噪声. 该方法有效地纠正了改善3D模型的镜像亮点和颜色不一致等问题.

科学领域:

  • 计算机视觉 计算机视觉
  • 三维重建的3D重建
  • 地理空间技术是什么

背景情况:

  • 3D重建技术面临着传感器限制和环境因素带来的挑战,导致纹理噪声.
  • 传统的方法由于数据量和噪音减轻困难而难以处理大规模场景.

研究的目的:

  • 在大规模3D重建中引入一个有效的结构噪声校正框架.
  • 为了解决诸如镜面亮点,颜色不一致和3D模型中的对象遮蔽等问题.

主要方法:

  • 组织 LiDAR 点和 RGB 图像以创建带有亮度值的彩色点云.
  • 使用voxel散列算法来加速几何重建和记忆效率.
  • 利用新的框架投票和邻居辅助染机制来消除噪音.

主要成果:

  • 实现了每秒100万点的处理速度,证明了实时适用性.
  • 在输出3D模型中显著降低了纹理噪声,提高了视觉质量.
  • 验证了框架在纠正多种纹理噪音类型方面的高级性能.

结论:

  • 拟议的基于全方位传感器系统的框架在大规模3D重建中显著提高了纹理质量.
关键词:
3D重建重建的3D重建框架融合框架框架融合框架图像传感器的成像传感器纹理 噪音 校正 纹理 噪音 校正这就是voxel的哈希.

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  • 创新的染机制有效地消除了常见的纹理噪声问题.
  • 该系统为高质量的3D场景重建提供了实用和高效的解决方案.