Disparity computation is a crucial step in the process of stereo 3D reconstruction, which has been a heavily investigated topic and one of the important problems in the field of computer vision. Many methods and approaches have been devised to provide a dense disparity map for a stereo image pair, with approaches roughly divided into local methods, which determine the correct disparity by choosing the value with an optimum matching cost in a local region, or global methods, which attempt to optimize a global energy equation for the entire scene. The global methods, while generally yielding better results, are more computationally intensive and are generally not suitable for real-time or embedded applications. The aim of this research was to propose new methods for disparity computation which would yield greater accuracy of the computed disparity map and faster computation by combining existing stereo algorithms with the three-dimensional recursive search algorithm (3DRS). The 3DRS algorithm was originally devised for motion estimation, frame rate up-conversion and de-interlacing in high definition televisions, and it can generate a coarse correspondence map (depending on the use, either the optical flow or disparity map) within a very short amount of time. In this dissertation, two methods based on the combination of the 3DRS algorithm with the local Winner-take-all method or the global Dynamic Programming method are presented. The proposed methods are evaluated using the Middlebury image set. It is shown that the proposed hybrid methods significantly outperform the original methods in execution time while maintaining or improving upon the accuracy of both methods. In addition, the hybrid methods are shown to exhibit greater robustness by reducing the dependency on specific external parameters. Scientific contribution: • A robust local method for computing stereo disparity maps initialized by the three-dimensional recursive search algorithm. • A robust global method for computing stereo disparity maps initialized by the three-dimensional recursive search algorithm. • A method for comparative analysis of the developed methods and the reference global and local stereo matching methods.