Stereo Matching with Optimal Adaptive Radiometric

A common assumption in stereo matching is that the corresponding pixels in stereo images have similar pixel values. Unfortunately, such an assumption may not be true due to radiometric variations in different views, leading to severely degraded matching results. In this letter, we propose a radiometrically invariant stereo matching algorithm called Optimal Local Adaptive Radiometric Compensation (LARAC). In LARAC, we approximate the spatially varying Pixel Value Correspondence

Function (PVCF) between a corresponding pixel pair as a locally consistent polynomial within an optimal local adaptive window. The optimal polynomial coefficients are obtained for each candidate disparity value and are used to compute the matching cost. Meanwhile, a self-correction property is achieved by the proposed LARAC, leading to reduced matching errors for the outlier pixels. Experimental results suggest that the proposed LARAC outperforms other state-of-the-art stereo matching algorithms.