Guthe, StefanGoesele, MichaelMatthias Hullin and Marc Stamminger and Tino Weinkauf2016-10-102016-10-102016978-3-03868-025-3-http://dx.doi.org/10.2312/vmv.20161345https://diglib.eg.org:443/handle/10.2312/vmv20161345The sheer size of volume data sampled in a regular grid requires efficient lossless and lossy compression algorithms that allow for on-the-fly decompression during rendering. While all hardware assisted approaches are based on fixed bit rate block truncation coding, they suffer from degradation in regions of high variation while wasting space in homogeneous areas. On the other hand, vector quantization approaches using texture hardware achieve an even distribution of error in the entire volume at the cost of storing overlapping blocks or bricks. However, these approaches suffer from severe blocking artifacts that need to be smoothed over during rendering. In contrast to existing approaches, we propose to build a lossy compression scheme on top of a state-of-the-art lossless compression approach built on non-overlapping bricks by combining it with straight forward vector quantization. Due to efficient caching and load balancing, the rendering performance of our approach improves with the compression rate and can achieve interactive to real-time frame rates even at full HD resolution.E.4 [Coding and Information Theory]Data Compaction and CompressionI.3.1 [Computer Graphics]Picture and Image GenerationGraphics processorsI.3.3 [Computer Graphics]Picture and Image GenerationViewing algorithms10.2312/vmv.2016134577-84