Dense Stereo Correspondence Using Combined Similarity Measurement

This paper presents a new real-time stereo correspondence method based on combined similarity measurement and guided filter. Many stereo correspondence methods use color intensity value as pixel similarity measurement, color intensity value is sensitive to noise, exposure, light and etc, so error correspondence rates of these methods are high. Gradient value is more robust to these factors than intensity, so we introduce the gradient value into the similarity measurement, and the linear combination of both measurements composes combined similarity measurement. Guided filter has edge-preserving character as bilateral filter, but runs faster than it, we use guided filter as adaptive support weight of the neighbored pixels in a finite squared support window. The experimental results demonstrate that our real-time approach performs much better compared with other local methods using different similarity measurements, whether in accuracy or robustness to radiometric distortions, according to the widely-used Middlebury stereo benchmarks.