1 November 2009 Fast viscosity solutions for shape from shading under a more realistic imaging model
Author Affiliations +
Optical Engineering, 48(11), 117201 (2009). doi:10.1117/1.3257283
Shape from shading (SFS) has been a classical and important problem in the domain of computer vision. The goal of SFS is to reconstruct the 3-D shape of an object from its 2-D intensity image. To this end, an image irradiance equation describing the relation between the shape of a surface and its corresponding brightness variations is used. Then it is derived as an explicit partial differential equation (PDE). Using the nonlinear programming principle, we propose a detailed solution to Prados and Faugeras's implicit scheme for approximating the viscosity solution of the resulting PDE. Furthermore, by combining implicit and semi-implicit schemes, a new approximation scheme is presented. In order to accelerate the convergence speed, we adopt the Gauss-Seidel idea and alternating sweeping strategy to the approximation schemes. Experimental results on both synthetic and real images are performed to demonstrate that the proposed methods are fast and accurate.
Guohui Wang, Jiuqiang Han, Honghai Jia, Xinman Zhang, "Fast viscosity solutions for shape from shading under a more realistic imaging model," Optical Engineering 48(11), 117201 (1 November 2009). https://doi.org/10.1117/1.3257283


Optical engineering

Computer programming

Light sources

Surface plasmons

Optical spheres

3D image reconstruction


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