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Stereoscopic phase differencing: Nonlinearities and multiscale synthesis
J. Monaco, A.C. Bovik and L.K. Cormack
IEEE Transactions on Image Processing
Abstract
Exploiting the quasi-linear relationship between local
phase and disparity, phase-differencing registration algorithms
provide a fast, powerful means for disparity estimation. Unfortunately,
these phase-differencing techniques suffer a significant
impediment: phase nonlinearities. In regions of phase nonlinearity,
the signals under consideration possess properties that
invalidate the use of phase for disparity estimation. This paper
uses the amenable properties of Gaussian white noise images
to analytically quantify these properties. The improved understanding
gained from this analysis enables us to better understand
current methodologies for detecting regions of phase instability.
Most importantly, we introduce a new, more effective means for
identifying these regions based on the second derivative of phase.
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