To reduce the sensitivity of the matching costs to complex optical distortions

such as vignetting

by fully exploiting the imaging model

a new matching cost using tensor analysis has been put forward. Compared with conventional costs

the proposed cost is resistive to complex distortions such as lens vignetting. Besides

it can reduce the matching ambiguity by reflecting the local image structure to a finer degree. We construct the proposed tensors rapidly on an integral image and measure their distance on the Riemannian manifold. In addition

a simple but effective disparity post-processing method is employed to further emend errors in the initial disparity map. Finally

the proposed method is compared with several other state-of-the-art disparity map generation methods under some challenging situations such as illumination variations and vignetting

the experimental results show that the proposed method is more robust and has higher disparity estimation accuracy.