3D Reconstruction of Weakly Textured Objects Based On Denoising Polarized Images

Traditional 3D visual reconstruction technology based on feature extraction is difficult to estimate the surface depth information of a smooth object with a single texture, while the polarization 3D reconstruction technology can recover the surface normal information from the image pixel by pixel, which has the characteristics of high precision, low texture dependence and strong material applicability. However, the normals recovered from the polarization information have the problem of multi-value ambiguity, which needs to be corrected before the accurate normal information can be recovered. At the same time, the image collected by the polarization camera contains a lot of noise, which will greatly affect the accuracy of reconstruction results. In this paper, the characteristics of polarization information are used to denoise the polarization image, and the reference normal information is used as the prior information for correcting the polarization normal. Firstly, the degree of polarization and angle of polarization are calculated based on the polarized image, then the two are fused and denoised by the Block Matching three-dimensional (BM3D) method, and then the multi-valued ambiguity of polarization normal is corrected according to the reference normal map. Finally, the corrected polarization normal is integrated to obtain a high-precision 3D shape of the object.