Abstract
In this paper, we formulate a novel trivariate biharmonic B-spline defined over bounded volumetric domain. The properties of bi-Laplacian have been well investigated, but the straightforward generalization from bivariate case to trivariate one gives rise to unsatisfactory discretization, due to the dramatically uneven distribution of neighbouring knots in 3D. To ameliorate, our original idea is to extend the bivariate biharmonic B-spline to the trivariate one with novel formulations based on quadratic programming, approximating the properties of localization and partition of unity. And we design a novel discrete biharmonic operator which is optimized more robustly for a specific set of functions for unevenly sampled knots compared with previous methods. Our experiments demonstrate that our 3D discrete biharmonic operators are robust for unevenly distributed knots and illustrate that our algorithm is superior to previous algorithms.
In this paper, we formulate a novel trivariate biharmonic B-spline defined over bounded volumetric domain. The properties of bi-Laplacian have been well investigated, but the straightforward generalization from bivariate case to trivariate one gives rise to unsatisfactory discretization, due to the dramatically uneven distribution of neighbouring knots in 3D. To ameliorate, our original idea is to extend the bivariate biharmonic B-spline to the trivariate one with novel formulations based on quadratic programming, approximating the properties of localization and partition of unity. And we design a novel discrete biharmonic operator which is optimized more robustly for a specific set of functions for unevenly sampled knots compared with previous methods. Our experiments demonstrate that our 3D discrete biharmonic operators are robust for unevenly distributed knots and illustrate that our algorithm is superior to previous algorithms.