Configurable Image Rectification and Disparity Refinement for Stereo Vision

Stereo matching is an essential topic in computer vision. However, the high complexity and massive computation restrict its applicability in real-time. This brief presents a pixel-level pipeline coprocessor for configurable binocular stereo rectification, region-optimized semi-global matching (SGM), left-right consistency checking (LRC), and disparity refinement. The contributions are summarized as follows: 1) Instead of storing the entire image of a large number of lines, the buffer size can be significantly reduced by the adjustment range computed according to the pre-calibrated coefficients. 2) An approximate divider with Newton iterations can reach the precision of 10−7 for high accuracy rectification with low latency. 3) A four-layer parallel two-stage pipeline is leveraged to address the computational bottleneck of the SGM, i.e., cost aggregation. 4) The pseudo-dual-port SRAMs and stacks mechanism solve the problem of inverse pixel flow in hole filling with low resource consumption. Finally, the proposed architecture is implemented on an Intel Stratix-IV FPGA and can process 144 frames ( $1024\mathbf {\times }768$ -pixel) per second at a maximum working frequency of 113.13 MHz.