Choosing the Best Interpolation Data in Images with Noise

How to Choose Interpolation Data in Images

We introduce and discuss shape based models for finding the best interpolation data when reconstructing missing regions in images by means of solving the Laplace equation. The shape analysis is done in the framework of Γ-convergence, from two different points of view. First, we propose a continuous PDE model and get pointwise information on the ”importance” of each pixel by a topological asympt...

Choosing the Best Bundle of Projects: A DEA Approach

Adaptively Choosing the Best Procedure for Selecting the Best System

This paper presents a method that uses initial sample data to choose between statistical procedures for identifying the simulated system with the best (maximum or minimum) expected performance. The method chooses the procedure that minimizes the additional number of simulation replications required to return a pre-specified probability guarantee. This problem may be encountered after a heuristi...

Choosing the Best Comparison Under the Circumstances

The Methodius Natural Language Generation systems generates personalized descriptions of objects from a collection. As part of the user modeling component, it creates comparisons between the current object being viewed and previous objects from the user history. We present our general algorithm for choosing the best comparison, which can be optimized to give the best result for different domain...

Choosing nodes in parametric curve interpolation

Perhaps a few words might be inserted here to avoid In parametric curve interpolation, the choice of the any possible confusion. In the usual function interpolation interpolating nodes makes a great deal of difference in the resulting curve. Uniform parametrization is generally setting, the problem is of the form P~ = (x, y~) where the x~ are increasing, and one seeks a real-valued unsatisfacto...