MULTIRESOLUTION RENDERING BASED ON GPGPU COMPUTING

The problem of visualizing large volumetric datasets is appealing for computation on the GPU. Nevertheless, the design of GPU volume rendering solutions must deal with the limited available memory in a graphics card. In this work, we present a system for multiresolution volume rendering which preprocesses the dataset dividing it into bricks and generating a compressed version by applying different levels of compression based on wavelets. The compressed volume is then stored in the GPU memory. For the later visualization process by texture mapping each brick of the volume is decompressed and rendered with a different resolution level depending on its distance to the camera. This approach computes most of the tasks in the GPU, thus minimizing the data transfers among CPU and GPU. We obtain competitive results for volumes of size in the range between 64 and 256.

A Model of Point Multiresolution Rendering Method

The paper proposed a data compression method in multiresolution structure and realized multiresolution rendering of point model by traversing the KD-tree breadth-first. It established the details control of multiresolution rendering, improved the drawing efficiency of point model. And a simulation study was carried out. Results show that the method could not only reduce the geometry data volume of point models directly, but also reduce the sampling point number without debasing the numerical precision of the model geometry data, so as to further reduce data volume of point model. In addition, the mixed rendering of geometric model point and rectangle in this method overcome the shortcoming that point model set is unsuitable for large flat surface.