Image-Space Acceleration for Direct Volume Rendering of Unstructured Grids using Joint Bilateral Upsampling

We describe a new image-space acceleration technique that allows real-time direct volume rendering of large unstructured volumes. Our algorithm operates as a simple post-process and can be used to improve the performance of any existing volume renderer that is sensitive to image size. A joint bilateral upsampling filter allows images to be rendered efficiently at a fraction of their original size, then upsampled at a high quality using properties that can be quickly computed from the volume. We show how our acceleration technique can be efficiently implemented with current GPUs and used as a post-process for a wide range of volume rendering algorithms and volumetric datasets. Image-Space Acceleration for Direct Volume Rendering of Unstructured Grids using Joint Bilateral Upsampling Steven P. Callahan and Cláudio T. Silva Abstract—We describe a new image-space acceleration technique that allows real-time direct volume rendering of large unstructured volumes. Our algorithm operates as a simple post-process and can be used to improve the performance of any existing volume renderer that is sensitive to image size. A joint bilateral upsampling filter allows images to be rendered efficiently at a fraction of their original size, then upsampled at a high quality using properties that can be quickly computed from the volume. We show how our acceleration technique can be efficiently implemented with current GPUs and used as a post-process for a wide range of volume rendering algorithms and volumetric datasets.We describe a new image-space acceleration technique that allows real-time direct volume rendering of large unstructured volumes. Our algorithm operates as a simple post-process and can be used to improve the performance of any existing volume renderer that is sensitive to image size. A joint bilateral upsampling filter allows images to be rendered efficiently at a fraction of their original size, then upsampled at a high quality using properties that can be quickly computed from the volume. We show how our acceleration technique can be efficiently implemented with current GPUs and used as a post-process for a wide range of volume rendering algorithms and volumetric datasets.