Evaluation of Shape from Shading Surface Reconstruction Quality for Liver Phantom

Bas, Mateusz; Spińczyk, Dominik

doi:10.1007/978-3-030-49666-1_7

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2022

2024

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Cited by 2 publications

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“…Shape-from-shading (SfS) is an important approach when it comes to recover the three dimensional shape of an object from a single image. In some imaging applications [1], [2], only one shot of the scene may be available. In such situations, SfS could be a preferable choice for 3D reconstruction.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Regularization Methods for Near-Light-Source Perspective Shape-from-Shading

Bazzi

Floor

Farup

2022

2022 IEEE International Conference on Image Processing (ICIP)

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3D shape reconstruction from images is an active topic in computer vision. Shape-from-Shading is an important approach which requires the surface properties and light source position to infer the 3D shape. A L2 regularizer is typically used to penalize the irradiance equation. In this article, anisotropic diffusion (AD) is introduced as a regularizer to solve the image irradiance equation. The method is then compared with L1 and L2 regularization methods, where all of the three techniques are formulated using gradient descent. Results shows that with AD, edges can be better preserved. AD shows lower depth error and higher correlation when compared with L1 and L2 regularization methods.

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Section: Introductionmentioning

confidence: 99%