18 October 1999 Using Gabor decomposition to improve dense disparity estimation
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Abstract
In this paper, we present a phase difference-based disparity estimation algorithm embedded in a cooperative multiscale scheme. We show that a reformulation of both the phase difference and the instantaneous frequency improves the density of the estimates. We define admissibility criteria of disparities. These criteria are based on both the magnitude and the phase linearity of the responses to increase the accuracy of the estimates but to the detriment of the density. By combining the multiscale estimates, the density is improved. Experimentations are reported for each criterion as well as for the multiscale combination. A performance analysis shows that the results obtained are very satisfactory.
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Mohammed H. Ouali, Djemel Ziou, Claude Laurgeau, "Using Gabor decomposition to improve dense disparity estimation", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365876; https://doi.org/10.1117/12.365876
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