Real-Time Edge-Sensitive Local Stereo Matching with Iterative Disparity Refinement

Abstract

Abstract. First, we present a novel cost aggregation method for stereo matching that uses two edge-sensitive shape-adaptive support windows per pixel region; one following the horizontal edges in the image, the other the vertical edges. Their combination defines the final aggregation window shape that closely follows all object edges and thereby achieves increased hypothesis confidence. Second, we present a novel iterative disparity refinement process and apply it to the initially estimated disparity map. The process consists of four rigorously defined and lightweight modules that can be iterated multiple times: a disparity cross check, bitwise fast voting, invalid disparity handling, and median filtering. We demonstrate that our iterative refinement has a large effect on the overall quality, resulting in smooth disparity maps with sharp object edges, especially around occluded areas. It can be applied to any stereo matching algorithm and tends to converge to a final solution. Finally, we perform a quantitative evaluation on various Middlebury datasets, showing an increase in quality of over several dB PSNR compared with their ground truth. Our whole disparity estimation algorithm supports efficient GPU implementation to facilitate scalability and real-time performance.

mproved Stereo Matching Algorithm based on Census Transform and Dynamic Histogram Cost Computation

“…[7] proposed essential matching cost absolute difference (AD) cost initialization for real-time high-quality system. The advanced AD formula sum of absolute differences (SAD) used by [8] to calculate for each pixel based on the disparity under consideration while zero-mean SSD (ZSSD) used by [9] which eliminates each patch of average intensity and used for the comparison between mean intensity of independent and each pixels.. Another familiar matching cost computation formula used is Normalized Cross Correlation (NCC) technique for generating matching costs.…”