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A simple and effective algorithm to construct a monotonicity preserving cubic Hermite interpolant for data with rapid variations is presented. Constraining the derivatives of the interpolant according to geometric considerations makes the interpolant consistent with local monotonicity properties of the data. Numerical examples are given that compare the quality and accuracy of the proposed interpolation method with other standard interpolants.
James M. Hyman (1983) studied this question.