Impact of noise on the polarimetric imaging based shape recovery of transparent objects

In the field of computer vision, specifically for applications aiming at the accurate 3D reconstruction of either natural or hand-made objects, only a few methods are able to recover the shape of transparent objects. Among these, polarimetric imagery has already proved its ability to deal with such objects. In this paper, after a short presentation of the theoretical background leading to the proposed approach for recovering the shape of transparent surfaces, various processing techniques for polarimetric data are described. In particular and firstly, the advantages implied by the use of measures relying on the full so-called Stokes vector are highlighted. Secondly, the method used for denoising multi-channel polarimetric image data, in order to improve the following surface recovery process, is introduced. Lastly, the efficiency of the suggested method is demonstrated through experimental results obtained using simulated surface data.