Research On Key Techniques Of Isosurface Extraction In 3D Scalar Field

Isosurface extraction is one of the most important means of visualization in 3D scalar fields,enabling users to understand intuitively and easily the information within the 3D space field.With the rapid development in hardware and software technology of computers,the scale of solving problems has been constantly expanding and the complexity has been constantly increasing.The traditional method of isosurface extraction faces many problems,such as the increasingly prominent demand of multitude extraction and the high complexity of time and space,seriously affecting the efficiency of data visual analysis.Aiming at the complexity of existing algorithms in time and space,a series of improved algorithms are proposed as follows to solve these problems in this paper.1.Aiming at the multi-isosurface extraction,a multi-isosurface acceleration extraction algorithm based on multi-active point searching is proposed.The algorithm utilizes the relationship among multiple isosurfaces to be extracted to find out the isosurfaces simultaneously containing multiple isosurfaces active voxels,so as to achieve the purpose of multi-isosurface extraction.Experimental results show that the proposed algorithm has a significant acceleration effect compared to the existing algorithms for multi-isosurface extraction.2.In order to reduce the space-time complexity of isosurface extraction,a sparsebased isosurface spatio-temporal optimization algorithm is proposed.By utilizing the characteristics of information sharing and the continuity of isosurfaces between grid cells,a BONO_Sparse algorithm based on sparse partitioning is proposed based on classical BONO algorithm,which can effectively reduce the space complexity of the algorithm and avoid double counting Reduce time complexity.Theoretical analysis and experimental results show that the BONO_Sparse algorithm has better space-time complexity than the BONO algorithm.3.In order to further optimize the time complexity of isosurface extraction,an isosurface acceleration extraction algorithm based on sparse partition-region tree is proposed in this paper.Aiming at the characteristics of the regional tree algorithm with better time complexity and poorer spatial complexity,the spatial tree algorithm is reduced by combining the regional tree algorithm with the previously proposed sparse partitioning idea,while preserving the superiority of the region tree the complexity.Theoretical analysis and experimental results show that the time complexity of sparse partitioningarea tree algorithm is better than that of BONO_Sparse algorithm,which has a better acceleration effect for small and medium-sized data.