Estimating Multiple Depths in Semi-transparent Stereo Images

A stereo algorithm that can estimate multiple depths in semi-transparent images is presented. The algorithm is based on a combination of phase analysis and canonical correlation analysis. The algorithm adapts filters in each local neighbourhood of the image in a way which maximizes the correlation between the filtered images. The adapted filters are then analysed to find the disparity. This is done by a simple phase analysis of the scalar product of the filters. For images with different but constant depths, a simple reconstruction procedure is suggested. Keywords: Stereo, Phase analysis, Canonical correlation analysis, Reconstruction. 1 Introduction An important feature of binocular vision systems is disparity, which is a measure of the shift between two corresponding neighbourhoods in a pair of stereo images. The disparity is related to the angle the eyes (cameras) must be be rotated relative to each other in order to focus on the same point in the 3-dimensional outside world. The ..