Traditional optical 3D shape measurement methods, such as light stripe triangulation, binary coding, and fringe projection, cannot acquire complete and correct 3D measurement results in the presence of interreflections. In this research, a 3D shape measurement method in the presence of interreflections based on light stripe triangulation is presented. The wrong measurement results caused by interreflections are excluded by the geometric constraints introduced by an additional camera. Each 3D point reconstructed by light stripe triangulation is projected onto the image plane of the additional camera to determine whether the 3D point is correct measurement result. Experimental results demonstrate that the proposed method can measure 3D shape in the presence of interreflections.
The blur of the optical system can cause inevitable degradation of acquired images. In this paper we present a novel method to measure the spatially-varying blur of the camera lens. We obtained the Discrete Cosine Transform (DCT) coefficients of the blur kernels by applying DCT single-pixel imaging to all the camera pixels. The spatially-varying blur kernels are then reconstructed by applying inverse DCT to the acquired coefficients. Experimental results show that the proposed method can acquire a more accurate blur kernel compared to the traditional Gaussian kernel.