NDLI: A Note on Some Phase Differencing Algorithms for Disparity Estimation

Content Provider	Springer Nature Link
Author	Cai, Li Dong Mayhew, John
Copyright Year	1997
Abstract	Disparity can be estimated from the local phase differences between a pair of stereo images after Gabor filterings. In this paper, some phase differencing algorithms are discussed from the point of view of numerical computation. They are all categorised as certain types of Newton iterations, hence are restricted by the preconditions of Newton iterations. Furthermore, a numerical sensitivity analysis is made for phase computation near its singularity points without referring to any specific filtering method. It makes clear that the numerical instability has its roots in the singularities of the phase functions themselves rather than in their derivatives, therefore severe errors cannot be properly reduced by Newton iterations. Hence, the singularity problem must be carefully treated for any disparity estimation using phase differencing techniques. In the case of foveal vision, such as target detection or vergence control, the central parts of scenes are of interest. A shift-trials algorithm is proposed to contain the effects of singularities instead of relying on detection and removal of singularity neighbourhoods through local computation. This algorithm directly tackles the singularity problem by posing the local disparity estimations as a minimisation of the phase differences of the left and right views in terms of a global matching residual norm. By a direct search for solution, no numerical derivative is needed, phase singularity can be tolerated and robust results are thus produced.
Starting Page	111
Ending Page	124
Page Count	14
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	22
Issue Number	2
e-ISSN	15731405
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	1997-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial Intelligence (incl. Robotics) Computer Imaging, Graphics and Computer Vision Image Processing Automation and Robotics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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