Real-Time Image Rectification and Stereo Reconstruction System on the GPU

The increase in computational power of consumer graphic cards has successfully motivated adaptation of stereo algorithms to this kind of hardware. In order to solve the stereo correspondence problem efficiently, the images need to be rectified and lens distortions need to be removed. This paper presents an efficient two step solution for rectifying and correcting lens distortions in images captured using a pair of stereo cameras. The first step consists of a one-time, off-line calculation of a look-up table, based on the calibration parameters, for each of the two cameras. The second step computes the final pixel intensities based on the pre-calculated mappings stored in the look-up table. The GPU implementation proposed makes use of the inherent parallelism in a cost-effective manner, making the method suitable for rectifying high resolution images in real-time. Results are compared against an optimized CPU-based implementation, written in assembly language using MMX instructions, for reference. The complete stereo reconstruction system was implemented and evaluated on a current generation GPU and offers a running time of 11ms for images with resolution 512×383.