Reconstruction algorithm for impenetrable rough surface profile under Neumann boundary condition

Sefer, Ahmet; Yapar, Ali

doi:10.1080/09205071.2021.2009381

Cited by 6 publications

(1 citation statement)

References 35 publications

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“…In order to satisfy the solution of the shielded Poisson equation and the boundary conditions in a given region, the algorithm bias error is reduced by introducing boundary constraints for solving the partial differential equation. There are three main types of boundary constraints: the Dirichlet boundary constraint [36], the Neumann boundary constraint and the Robin boundary constraint [37,38]. At the endpoints it is generally written in the form Ay + By' = C.…”

Section: The Neumann Boundary Constraintmentioning

confidence: 99%

An Improved Poisson Surface Reconstruction Algorithm based on the Boundary Constraints

Liu¹,

Wang²,

Tahir³

et al. 2023

IJACSA

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The usage of the point cloud surface reconstruction to generate high-precision 3D models has been widely applied in various fields. In order to deal with the problems of insufficient accuracy, pseudo-surfaces and high time cost caused by the traditional surface reconstruction algorithms of the point cloud data, this paper proposes an improved Poisson surface reconstruction algorithm based on the boundary constraints. For large density point cloud data obtained from 3D laser scanning, the proposed method firstly uses an octree instead of the KD-tree to search the near neighborhood; then, it uses the Open Multi-Processing (OpenMP) to accelerate the normal estimation based on the moving least squares algorithm; meanwhile, the leastcost spanning tree is employed to adjust the consistency of the normal direction; and finally a screened Poisson algorithm with the Neumann boundary constraints is proposed to reconstruct the point cloud. Compared with the traditional methods, the experiments on three open datasets demonstrated that the proposed method can effectively reduce the generation of pseudosurfaces. The reconstruction time of the proposed algorithm is about 16% shorter than that of the traditional Poisson reconstruction algorithm, and produce better reconstruction results in the term of quantitative analysis and visual comparison.

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Section: The Neumann Boundary Constraintmentioning

confidence: 99%

An Improved Poisson Surface Reconstruction Algorithm based on the Boundary Constraints

Liu¹,

Wang²,

Tahir³

et al. 2023

IJACSA

View full text Add to dashboard Cite

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Reconstruction of rough surfaces from a single receiver at grazing angle

Chen,

Spivack,

Rath Spivack

2024

IET Science Measure & Tech

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This article develops a method for recovering a one‐dimensional rough surface profile from scattered wave field, using a single receiver and repeated measurements when the surface is moving with respect to source and receiver. This extends a previously introduced marching method utilizing low grazing angles, and addresses the key issue of the requirement for many simultaneous receivers. The algorithm recovers the surface height below the receiver point step‐by‐step as the surface is moved, using the parabolic wave integral equations. Numerical examples of reconstructed surfaces demonstrate that the method is robust in both Dirichlet and Neumann boundary conditions, and with respect to different roughness characteristics and measurement noise.

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Recovery of impenetrable rough surface profiles via CNN-based deep learning architecture

Aydin

Budak

Sefer

et al. 2022

International Journal of Remote Sensing

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Reconstruction algorithm for impenetrable rough surface profile under Neumann boundary condition

Cited by 6 publications

References 35 publications

An Improved Poisson Surface Reconstruction Algorithm based on the Boundary Constraints

An Improved Poisson Surface Reconstruction Algorithm based on the Boundary Constraints

Reconstruction of rough surfaces from a single receiver at grazing angle

Recovery of impenetrable rough surface profiles via CNN-based deep learning architecture

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