Real-Time Hardware Stereo Matching Using Guided Image Filter

Abstract

Stereo matching is a key step in stereo vision systems that require high accurate depth information and real-time processing of high definition image streams. This work presents a high-accuracy hardware implementation for the stereo matching based on the guided image filter, which is an edge-preserving filter and simplifies the adaptive support window algorithm. The coefficients in the guided image filter are calculated by the proposed mean filter tree structure, which saves hardware resources by sharing large amounts of additions among filter operations. The reference image is enhanced using Laplacian Filter, which improves the accuracy for the discontinuous disparity regions. Moreover, an 8×8 matching window and customized ping-pong caches are used to improve the whole throughputs. The proposed hardware architecture is implemented on a Cyclone IV FPGA resulting in a throughput of 1080p resolution images at 80fps with high accuracy of disparity.