2D phase-based matching in uncalibrated images
A novel 2D phase-based matching approach is proposed to resolve the general stereo image matching problem. It is different from the current uncalibrated matching techniques, most of which obtain 2D dense disparity map after the epipolar geometry has been recovered. In this paper, the disparity is directly estimated by simply establishing correspondences between quaternionic phase structures of two QWF (quaternion wavelet filtered) images. Real and short-length biorthogonal wavelet bases are exploited to build linear-phase quaternion wavelet filters (LPQWFs). Once phases are extracted from the QWF image pair, the disparity estimation is formed as a minimization process of a cost function, which is formulated as a similarity measure for comparing quaternion wavelet phases. With regard to the mismatches near phase singularities, phase stability constraints are imposed on cost aggregation stage. And multi-scale matching strategy is introduced to avoid phase wrapping problem and improve convergence speed. The experimental results are encouraging in various image pairs.