A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vertical and horizontal disparities from phase
ECCV 90 Proceedings of the first european conference on Computer vision
Stability of Phase Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized convolution for extraction of image features in the primary domain
Machine Graphics & Vision International Journal
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Point-to-point correspondence is one of the most challenging problems in stereo image matching. Correspondence or disparity established between points of two images is the result of stereo matching. The paper presents new point-to-point correspondence algorithms based on wavelet analysis. Each image in the pair is decomposed into an approximation, and details go through the coarse to fine level. For the above decomposition, multiresolution analysis is used. In the proposed approach, a disparity is found in the wavelet transform space. An extension and generalization of phase-based method is presented. The classical Gabor's approach is extended to real wavelets. Differences of amplitudes (grey levels) in images which frequently appear in stereo pairs are eliminated. Invariance of the disparity determination with respect to amplitude changes may be achieved by choosing an appropriate pair of wavelet systems. The achieved result is broader than the classical one, based on the Gabor wavelet and the phase method. Numerical experiments with images have confirmed this approach. Finally, three concepts (see Section 5) are presented to analyse the problem of disparity determination globally.