Noise Analysis of a SFS Algorithm Formulated under Various Imaging Conditions

Many different shape from shading (SFS) algorithms have emerged during the last three decades. Recently, we proposed [1] a unified framework that is capable of solving the SFS problem under various settings of imaging conditions representing the image irradiance equation of each setting as an explicit Partial Differential Equation (PDE). However, the result of any SFS algorithm is mainly affected by errors in the given image brightness, either due to image noise or modeling errors. In this paper, we are concerned with quantitatively assessing the degree of robustness of our unified approach with respect to these errors. Experimental results have revealed promising performance against noisy images but has also lacked in reconstructing the correct shape due to error in the modeling process. This result emphasizes the need for robust algorithms for surface reflectance estimation to aid SFS algorithms producing more realistic shapes.