Total Differential Photometric Mesh Refinement with Self-Adapted Mesh Denoising

Variational mesh refinement is a crucial step in multiview 3D reconstruction. Existing algorithms either focus on recovering mesh details or focus on suppressing noise. Approaches with consideration of both are lacking. To address this limitation, we proposed a new variational mesh refinement method...

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Bibliographic Details
Published in:Photonics 2023-01, Vol.10 (1), p.20
Main Authors: Qu, Yingjie, Yan, Qingsong, Yang, Junxing, Xiao, Teng, Deng, Fei
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Consistency
Cross correlation
Grid refinement (mathematics)
mesh denoising
Mesh generation
Methods
Noise
Noise reduction
photogrammetry
photometric mesh refinement
Self adaptive control systems
Semantics
surface reconstruction
variational mesh refinement
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Summary:Variational mesh refinement is a crucial step in multiview 3D reconstruction. Existing algorithms either focus on recovering mesh details or focus on suppressing noise. Approaches with consideration of both are lacking. To address this limitation, we proposed a new variational mesh refinement method named total differential mesh refinement (TDR), which mainly included two improvements. First, the traditional partial-differential photo-consistency gradient used in the variational mesh refinement method was replaced by the proposed total-differential photo-consistency gradient. With consideration of the photo-consistency correlation between adjacent pixels, our method can make photo-consistency achieve a more effective convergence than traditional approaches. Second, we introduced the bilateral normal filter with a novel self-adaptive mesh denoising strategy into the variational mesh refinement. This strategy maintains a balance between detail preservation and effective denoising via the zero-normalized cross-correlation (ZNCC) map. Various experiments demonstrated that our method is superior to traditional variational mesh refinement approaches in both accuracy and denoising effect. Moreover, compared with the mesh generated by open-source and commercial software (Context Capture), our meshes are more detailed, regular, and smooth.
ISSN:2304-6732
2304-6732
DOI:10.3390/photonics10010020