Two-dimensional regularized disparity estimation based on the Gabor transform

This paper presents a disparity estimation algorithm that combines three different kinds of techniques: Gabor transform, variational refinement and region-based affine parameter estimation for disparity calculation. The Gabor transform is implemented using a set of quadrature-pair filters for estimating the two-dimensional cor- respondences between the two images without the calibration information, and the estimated coarse disparity maps are applied to a variational refinement process which involves solving a set of partial differential equations (PDEs). Then the refined disparity values are used with the image segmentation information so that the parameters of affine transforms for the correspondence of each region can be calculated by singular value decomposition (SVD), and these affine parameters can be applied in turn to bring more refined disparity maps.

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