Constraining global interpolation methods for sparse data volume visualization

摘要

The study of sparse data volume visualization further expands the application scope of volume visualization from scientific study and medical imaging into engineering applications. The existing two-step approach to sparse data volume visualization faces three dilemmas: the negative-value dilemma, the zero-value dilemma, and the correctness dilemma. This paper presents three constraining techniques that can be used to alleviated these dilemmas. The con- straints are point constraint, value constraint, and local constraint.