Volume rendering is an effective technique for visualizing sampled scalar or vector fields in the three dimensional space. A subset of this technique generates images by computing 2D projections of a colored semi-transparent volume where the color and opacity at each point are derived from the data using local operators. Since all voxels participate in the generation of each image, rendering time grows linearly with the size of the data set. Therefore, high quality images take tens of seconds or minutes to generate on current workstations.
Fast volume rendering algorithm, known as the shear and warp method, is implemented and compared with the previous method. The drawback of this method is aliasing effect caused by reducing the calculations to save the rendering time.
In this thesis, the degradation of image caused by the shear and warp method is analyzed, and a new data classification function is suggested for eliminating the aliasing artifacts. The volume rendering system using the proposed function provides the improved image quality without increasing storage space and rendering time.
