The fast computation of disparity from phase differences

The authors demonstrate how the approach of recovering disparity from the measurement of local phase differences can be accomplished without the computational expense exhibited by previous algorithms.

Abstract

Previous work has demonstrated that the task of recovering local disparity measurements can be reduced to the task of measuring the local phase between bandpass signals extracted from the left and right cameras. In computing this local phase difference, earlier algorithms expressed the computational task as a nonlinear differential equation to be solved at each image point. Although this approach has great appeal as a model for biological disparity measurement, the solving of a differential equation at a large number of image points and disparities makes the algorithm unsuitable for serial digital computer applications. Here, the authors demonstrate how the approach of recovering disparity from the measurement of local phase differences can be accomplished without the computational expense exhibited by previous algorithms. This disparity measurement technique is embedded within a simple coarse-to-fine stereopsis similar to the algorithm proposed by H.K. Nishihara (1984) and the resulting algorithm is applied to a number of stereo pairs.>