The wide majority of current state-of-the-art compressed GPU volume renderers are based on block-transform coding, which is susceptible to blocking artifacts, particularly at low bit-rates. In this paper the authors address the problem for the first time, by introducing a specialized deferred filtering architecture working on block-compressed data and including a novel deblocking algorithm. The architecture efficiently performs high quality shading of massive datasets by closely coordinating visibility- and resolution-aware adaptive data loading with GPU-accelerated per-frame data decompression, deblocking, and rendering. A thorough evaluation including quantitative and qualitative measures demonstrates the performance of our approach on large static and dynamic datasets including a massive 512^4 turbulence simulation (256GB), which is aggressively compressed to less than 2 GB, so as to fully upload it on graphics board and to explore it in real-time during animation.
(Fabio Marton, José Antonio Iglesias Guitián, Jose Díaz and Enrico Gobbetti: “Real-time deblocked GPU rendering of compressed volumes”. Proc. 19th International Workshop on Vision, Modeling and Visualization (VMV), pp. 167-174, Oct. 2014. [WWW])