Stereo matching has been widely used in many fields, such as viewpoint interpolation, feature detection system and free-view TV. However, the long processing time of stereo matching algorithms has been the major bottleneck that limits their real-time applications. During the past decades, many implementation platforms and corresponding algorithm adaptations are proposed to solve the processing time problem. Although notable real-time performances have been achieved, these works rarely satisfy both real-time processing and high stereo matching quality requirements. In this thesis, we propose a stereo matching algorithm suitable for hardware implementation based on the VariableCross and the MiniCensus algorithm. Furthermore, we provide parallel computing hardware design and implementation of the proposed algorithm. The developed stereo matching hardware modules are instantiated in an SoC environment and implemented on a single EP3SL150 FPGA chip. The experimental results suggest that our work has achieved high speed real-time processing with programmable video resolutions, while preserving high stereo matching accuracy. The online benchmarks also prove that this work delivers leading matching accuracy among declared real-time implementations, with only 8.2% averaged benchmark error rate. We have also achieved 60 frames per second for 1024 × 768 high-definition stereo matching, which is the fastest high-definition stereo matching to the best of our knowledge.