Robust shape from polarisation and shading

In this paper, we present an approach to robust estimation of shape from single-view multi-spectral polarisation images. The developed technique tackles the problem of recovering the azimuth angle of surface normals robust to image noise and a low degree of polarisation. We note that the linear least-squares estimation results in a considerable phase shift from the ground truth in the presence of noise and weak polarisation in multispectral and hyperspectral imaging. This paper discusses the utility of robust statistics to discount the large error attributed to outliers and noise. Combining this approach with Shape from Shading, we fully recover the surface shape. We demonstrate the effectiveness of the robust estimator compared to the linear least-squares estimator through shape recovery experiments on both synthetic and real images.