Progressive iterative approximation for regularized least square bivariate B-spline surface fitting

作者：

Highlights：

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• RLSPIA extends the PIA property to a set of bivariate non-tensor blending bases.

• RLSPIA generalizes the scope of PIA property to a set of linear dependent bases.

• RSPIA has faster convergence rate by using the accelerating term.

• RSPIA is flexible to impose additional operation, such as surface fairing.

摘要

•RLSPIA extends the PIA property to a set of bivariate non-tensor blending bases.•RLSPIA generalizes the scope of PIA property to a set of linear dependent bases.•RSPIA has faster convergence rate by using the accelerating term.•RSPIA is flexible to impose additional operation, such as surface fairing.

论文关键词：Progressive iterative approximation,Bivariate B-spline surface,Regularized least square,Surface fitting,Successive over-relaxation iteration

论文评审过程：Received 28 February 2017, Revised 6 June 2017, Available online 19 June 2017, Version of Record 6 July 2017.

论文官网地址：https://doi.org/10.1016/j.cam.2017.06.013