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TENet:注意力频率边缘增强的3D纹理增强网络

Ying Wang^1,2, Tao Fu^1,2, Yu Zhou³

¹School of Aerospace, Harbin Institute of Technology Shenzhen, Shenzhen 518055, China.

Sensors (Basel, Switzerland)

|February 13, 2025

概括

研究人员开发了一种新的3D纹理增强网络 (TENet),以提高从光谱学获得的3D模型的质量. 这种方法提高了细节和恢复了边缘,显著提高了表面纹理质量和重建精度.

科学领域:

计算机视觉计算机视觉
3D重建的3D重建
这是一种摄影计量技术 (photogrammetry).

背景情况:

斜摄像度图像通常会导致3D重建,由于分辨率不均和细节模糊,表面质感质量差,特别是用于建筑立面.
现有的方法很难有效地恢复3D模型中的细粒度纹理和关键边缘特征.

研究的目的:

引入一个新的注意力频率边缘增强的3D纹理增强网络 (TENet) 和一个全面的管道来提高3D纹理质量.
为了增强从摄影计量数据生成的3D模型的度,边缘精度和整体表面纹理.

主要方法:

开发了TENet,结合了注意力机制和频域技术来增强纹理.
在管道中引入了一个区域分辨率自适应增强模块 (RAEM) 和一个频域边缘增强机制 (FDEEM).
应用了适用于3D模型的2D纹理超分辨率技术.

主要成果:

在改善3D纹理质量和重建性能方面,TENet显著优于现有方法.
除研究证实了单个组件 (RAEM,FDEEM) 在增强3D纹理重建方面的有效性.
通过对现实世界的应用进行验证,TENet有效地减少了边缘工件,并在3D表面模型中恢复了清晰,准确的纹理.

结论:

拟议的TENet和增强管道为 photogrammetry 中改善 3D 纹理质量提供了强大的解决方案.
该方法在3D模型,特别是建筑立面的细节修复和文物减少方面取得了显著的改进.
TENet为需要高保真度3D表面表示的应用提供了宝贵的工具.

关键词:

3D表面纹理增强增强 3D表面纹理增强频域增强频率域的增强这是一种斜摄影仪 (oblique photogrammetry).自我注意力机制机制

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