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Multiresolution Phase-Based Bidirectional Stereo Matching with Provision for Discontinuity and Occlusion

Stereo image matching is the most robust and domain-independent way of reconstructing object surfaces from perspective images. Dense feature space matching is desirable because it constructs a disparity field without arbitrary selection of interest points for individual matching. Multiresolution or coarse-to-fine strategies have been shown to be effective in overcoming the inherent ambiguities of dense feature space matching. We use Gabor phase as the basis for dense multiresolution matching, as it is a stable, ubiquitous feature of a signal. The use of Gabor-like complex wavelets enables the efficient transformation of images to Gabor-phase-based feature pyramids. Disparity discontinuity and occlusions are the major potential disruptions to coarse-to-fine image matching. Through perspective geometry, we show that depth discontinuities are the direct cause of the discontinuity of disparity field, and bidirectional matching is required to detect disparity discontinuities (and their dual counterpart, occlusions) in both views. To handle these, a global objective function incorporating feature similarity, disparity smoothness, and discontinuity/occlusions is established under the maximuma posterioriprobability criterion and equivalently transformed into a minimum description length criterion. A general procedure, using stochastic relaxation with special provision for occlusions, is developed for minimising the objective function. The result is a disparity field which is regularised in the continuous regions, while the discontinuities and occlusions are detected and preserved. Some results from an aerial terrain image pair indicate the applicability of this approach.