Image simplification using a robust reconstruction filter

Details Image simplification using a robust reconstruction filter Image simplification using a robust reconstruction filter

2006-09-05

2006-09-05

Mehta, Bhavesh M. (Department: 2624)

Image analysis

Image enhancement or restoration

Artifact removal or suppression

C382S276000

Reexamination Certificate

active

07103229

ABSTRACT:
A method simplifies a data structure representing physical measurements of a real-world phenomena, such as an image of a scene of an object. Input data are first acquired, sensed, or measured. If the data are acquired with a camera, then measurement errors for data points in the data structure are not normally distributed. Therefore, an error term for each data point is constructed according to a Lorentzian estimator. The error term can be determined by taking a difference between the value of the data point, and the value at the data point when a model is fitted to the data structure. The error term is then minimized using a downhill simplex minimization process. Finally, each data point is adjusted by the minimized error term to produce a simplified data structure of the real-world phenomena.

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“Numerical Recipes in C: The Art of Scientific Computing”, (ISBN 0-521-43108-5), 1988-1992, Cambridge University Press, pp. 699-706.
Black and Rangarajan, “On the Unification of Line Process, Outliner Rejection, and Robust Statistics with Applications in Early Vision,” International Journal of Computer Vision (in-press), Submitted Nov. 1993.

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