Compressed Volume Rendering Based On Transform Coding

Volume rendering is one of the main methods in scientific visualization field. The intrinsic information of volume dataset can be visualized interactively by volume rendering. Volume rendering is also known as direct volume rendering, for no intermediate geometry primitives are generated during its visualization process. It can generate the image of dataset with high quality details and context. Volume rendering can be applied in many fields including medical science, meteorology and geological exploration.As the development of scientific instruments, the size of dataset generated has been increased dramatically. Such large scale datasets pose immense challenges to volume rendering. Hardware-accelerated volume rendering using the GPU is now the standard approach for real-time volume rendering, although limited graphics memory can present a problem when rendering large volume data sets. Volumetric compression in which the decompression is coupled to rendering has been shown to be an effective solution to this problem; however, most existing techniques were developed in the context of software volume rendering, and all but the simplest approaches are prohibitive in a real-time hardware-accelerated volume rendering context. In this paper we present a novel block-based transform coding scheme designed specifically with real-time volume rendering in mind, such that the decompression is fast without sacrificing compression quality. This is made possible by consolidating the inverse transform with dequantization in such a way as to allow most of the reprojection to be precomputed. Furthermore, we take advantage of the freedom afforded by offline compression in order to optimize the encoding as much as possible while hiding this complexity from the decoder. In this context we develop a new block classification scheme which allows us to preserve perceptually important features in the compression. The result of this work is an asymmetric transform coding scheme that allows very large volumes to be compressed and then decompressed in real-time while rendering on the GPU.