Space and time efficient isosurface extraction

The constantly growing size of datasets over the past two decades has put new requirements on the space and time efficiency of isosurface extraction methods. We present a novel approach to fast isosurface extraction, which significantly shortens the preprocessing time and lowers the space requirements. A new computationally inexpensive technique is proposed for transformation of the original volume data into an alternative 1D space. A proper space efficient data structure, built over the transformed data, is used for isosurface extraction. The relative simplicity of the proposed method allows its easy implementation. We demonstrate the low space and time requirements of the proposed approach by a comparison with current state-of-the-art methods applied to real-world datasets.