Phase-based disparity estimation: a spatial approach

This paper presents a new 2D disparity-estimation algorithm. Disparity is calculated from an estimation of the phase difference between two views of the same scene from different angles. This phase difference is obtained by convolution of the two views with the Gaussian function and its first two derivatives. Since the disparities obtained often contain errors, we use a regularization model in order to smooth the disparity by preserving the structure of objects. While the models used were simple and noise-free, the results obtained are promising