Confocal Disparity Estimation and Recovery of Pinhole Image for Real-Aperture Stereo Camera Systems
A single dense depth estimation using stereo or defocus cannot produce a reliable result due to the ambiguity problem. In this paper, we propose a novel anisotropic disparity estimation embedding a stereo confocal constraint for real-aperture stereo camera systems. If the focal length of a real-aperture stereo camera is just changed, the depth range is localized in a focused object which can be discriminated from defocused blurring. The focal depth plane is estimated by the displacement of tensors which are derived from generalized 2D Gaussian, since the point spread functions (PSF) in defocused blurring can be approximated by a shift-invariant Gaussian function. We localize the isotropic propagation in blurring over invariance by a sparse Laplacian kernel in Poisson solution. The matching of real-aperture stereo images is performed by observing the focal consistency. However, the isotropic propagation cannot exactly hold a non-parallel surface to the lens plane i.e., unequifocal surface. An anisotropic regularization term is employed to suppress the isotropic propagation near the non-parallel surface boundary. Our method achieves an accurate dense disparity map by sampling the disparities in focal points from multiple defocus stereo images. The pels in focal points are utilized to recover the pinhole image (i.e. an ideally focused image for all different depths).