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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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Published in: | Photonics 2023-01, Vol.10 (1), p.20 |
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creator | Qu, Yingjie Yan, Qingsong Yang, Junxing Xiao, Teng Deng, Fei |
description | 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. |
doi_str_mv | 10.3390/photonics10010020 |
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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.</description><identifier>ISSN: 2304-6732</identifier><identifier>EISSN: 2304-6732</identifier><identifier>DOI: 10.3390/photonics10010020</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>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</subject><ispartof>Photonics, 2023-01, Vol.10 (1), p.20</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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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 |
title | Total Differential Photometric Mesh Refinement with Self-Adapted Mesh Denoising |
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