Interactive Editing of GigaSample Terrain Fields

Previous terrain rendering approaches have addressed the aspect of data compression and fast decoding for rendering, but applications where the terrain is repeatedly modified and needs to be buffered on disk have not been considered so far. Such applications require both decoding and encoding to be...

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Published in:	Computer graphics forum Vol. 31; no. 2pt2; pp. 383 - 392
Main Authors:	Treib, Marc, Reichl, Florian, Auer, Stefan, Westermann, Rüdiger
Format:	Journal Article
Language:	English
Published:	Oxford, UK Blackwell Publishing Ltd 01.05.2012
Subjects:	Computer graphics Computer science Data compression Editing I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism I.4.2 [Image Processing and Computer Vision]: Compression (Coding) Information management Studies
ISSN:	0167-7055, 1467-8659
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Abstract	Previous terrain rendering approaches have addressed the aspect of data compression and fast decoding for rendering, but applications where the terrain is repeatedly modified and needs to be buffered on disk have not been considered so far. Such applications require both decoding and encoding to be faster than disk transfer. We present a novel approach for editing gigasample terrain fields at interactive rates and high quality. To achieve high decoding and encoding throughput, we employ a compression scheme for height and pixel maps based on a sparse wavelet representation. On recent GPUs it can encode and decode up to 270 and 730 MPix/s of color data, respectively, at compression rates and quality superior to JPEG, and it achieves more than twice these rates for lossless height field compression. The construction and rendering of a height field triangulation is avoided by using GPU ray‐casting directly on the regular grid underlying the compression scheme. We show the efficiency of our method for interactive editing and continuous level‐of‐detail rendering of terrain fields comprised of several hundreds of gigasamples.
AbstractList	Previous terrain rendering approaches have addressed the aspect of data compression and fast decoding for rendering, but applications where the terrain is repeatedly modified and needs to be buffered on disk have not been considered so far. Such applications require both decoding and encoding to be faster than disk transfer. We present a novel approach for editing gigasample terrain fields at interactive rates and high quality. To achieve high decoding and encoding throughput, we employ a compression scheme for height and pixel maps based on a sparse wavelet representation. On recent GPUs it can encode and decode up to 270 and 730 MPix/s of color data, respectively, at compression rates and quality superior to JPEG, and it achieves more than twice these rates for lossless height field compression. The construction and rendering of a height field triangulation is avoided by using GPU ray-casting directly on the regular grid underlying the compression scheme. We show the efficiency of our method for interactive editing and continuous level-of-detail rendering of terrain fields comprised of several hundreds of gigasamples. [PUBLICATION ABSTRACT] Previous terrain rendering approaches have addressed the aspect of data compression and fast decoding for rendering, but applications where the terrain is repeatedly modified and needs to be buffered on disk have not been considered so far. Such applications require both decoding and encoding to be faster than disk transfer. We present a novel approach for editing gigasample terrain fields at interactive rates and high quality. To achieve high decoding and encoding throughput, we employ a compression scheme for height and pixel maps based on a sparse wavelet representation. On recent GPUs it can encode and decode up to 270 and 730 MPix/s of color data, respectively, at compression rates and quality superior to JPEG, and it achieves more than twice these rates for lossless height field compression. The construction and rendering of a height field triangulation is avoided by using GPU ray‐casting directly on the regular grid underlying the compression scheme. We show the efficiency of our method for interactive editing and continuous level‐of‐detail rendering of terrain fields comprised of several hundreds of gigasamples.
Author	Treib, Marc Westermann, Rüdiger Auer, Stefan Reichl, Florian
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References_xml	– reference: Dick C., Schneider J., Westermann R.: Efficient geometry compression for GPU-based decoding in realtime terrain rendering. Computer Graphics Forum 28, 1 (2009), 67-83. 2, 3 – reference: Gobbetti E., Marton F., Cignoni P., Di Benedetto M., Ganovelli F.: C-BDAM - compressed batched dynamic adaptive meshes for terrain rendering. Computer Graphics Forum 25, 3 (2006), 333-342. 2 – reference: Cohen A., Daubechies I., Feauveau J. C.: Biorthogonal bases of compactly supported wavelets. Comm. on Pure and Applied Mathematics 45, 5 (1992), 485-560. 5 – reference: Taubman D. S., Marcellin M. W.: JPEG 2000: Image Compression Fundamentals, Standards and Practice. Kluwer Academic Publishers, 2001. 3 – reference: Wong T.-T., Leung C.-S., Heng P.-A., Wang J.: Discrete wavelet transform on consumer-level graphics hardware. IEEE Trans. Multimedia 9, 3 (2007), 668-673. 3 – reference: Wang X., Zheng X., Yin Q.: Large scale terrain compression and real-time rendering based on wavelet transform. In Proc. Computational Intelligence and Security (CIS) (2008), vol. 2, pp. 489-493. 3 – reference: Malvar H., Sullivan G.: YCoCg-R: A Color Space with RGB Reversibility and Low Dynamic Range. Joint Video Team (JVT) of ISO/IEC MPEG & ITU-T VCEG, 2003. 5 – reference: Van Der Laan W.J., Jalba A. C., Roerdink J. B. T. M.: Accelerating wavelet lifting on graphics hardware using CUDA. IEEE Trans. Parallel and Distributed Systems 22, 1 (2011), 132-146. 2, 3, 5 – reference: Bruneton E., Neyret F.: Real-time rendering and editing of vector-based terrains. Computer Graphics Forum 27, 2 (2008), 311-320. 3 – reference: Atlan S., Garland M.: Interactive multiresolution editing and display of large terrains. Computer Graphics Forum 25, 2 (2006), 211-223. 2 – reference: Lambers M., Kolb A.: Dynamic terrain rendering. 3D Research 1, 4 (2010), 1-8. 2 – reference: Abu-Mostafa Y. S., McEliece R. J.: Maximal codeword lengths in huffman codes. Computers & Mathematics with Applications 39, 11 (2000), 129-134. 7 – reference: Tenllado C., Setoain J., Prieto M., Pinuel L., Tirado F.: Parallel implementation of the 2D discrete wavelet transform on graphics processing units: Filter bank versus lifting. IEEE Trans. Parallel and Distributed Systems 19, 3 (2008), 299-310. 3 – reference: Podlozhnyuk V.: Histogram calculation in CUDA. NVIDIA Corp., 2007. 7 – reference: Pradhan B., Sandeep K., Mansor S., Ramli A. R., Sharif A. R. B. M.: Second generation wavelets based GIS terrain data compression using Delaunay triangulation. Engineering Computations 24, 2 (2007), 200-213. 3 – reference: Pajarola R., Gobbetti E.: Survey of semi-regular multiresolution models for interactive terrain rendering. Visual Computer 23, 8 (2007), 583-605. 1, 2 – reference: Van Waveren J. M. P.: Real-Time Texture Streaming & Decompression. Tech. rep., id Software, Inc., 2006. 8 – reference: Van Waveren J. M. P., Castaño I.: Real-Time YCoCg-DXT Compression. 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Multimedia – start-page: 418 year: 2007 end-page: 422 – volume: 28 start-page: 67 issue: 1 year: 2009 end-page: 83 article-title: Efficient geometry compression for GPU‐based decoding in realtime terrain rendering publication-title: Computer Graphics Forum – start-page: 551 year: 2008 end-page: 559 – start-page: 37 year: 2007 end-page: 44 – year: 2008 – volume: 19 start-page: 299 issue: 3 year: 2008 end-page: 310 article-title: Parallel implementation of the 2D discrete wavelet transform on graphics processing units: Filter bank versus lifting publication-title: IEEE Trans. Parallel and Distributed Systems – year: 2006 – start-page: 43 year: 2009 end-page: 50 – start-page: 153 year: 1995 end-page: 160 – volume: 2 start-page: 489 year: 2008 end-page: 493 article-title: Large scale terrain compression and real‐time rendering based on wavelet transform publication-title: Proc. Computational Intelligence and Security (CIS) – start-page: 26 year: 2009 end-page: 35 – volume: 22 start-page: 132 issue: 1 year: 2011 end-page: 146 article-title: Accelerating wavelet lifting on graphics hardware using CUDA publication-title: IEEE Trans. Parallel and Distributed Systems – ident: e_1_2_8_21_2 doi: 10.1145/1730804.1730815 – ident: e_1_2_8_35_2 doi: 10.1109/TPDS.2010.143 – ident: e_1_2_8_16_2 – ident: e_1_2_8_32_2 – ident: e_1_2_8_5_2 doi: 10.1007/978-3-642-14122-5_6 – ident: e_1_2_8_17_2 doi: 10.1111/j.1467-8659.2006.00952.x – ident: e_1_2_8_19_2 – ident: e_1_2_8_8_2 – volume-title: JPEG 2000: Image Compression Fundamentals, Standards and Practice year: 2001 ident: e_1_2_8_33_2 – ident: e_1_2_8_30_2 – ident: e_1_2_8_12_2 doi: 10.1002/cpa.3160450502 – start-page: 413 volume-title: Scientific Computing with Multicore and Accelerators year: 2011 ident: e_1_2_8_31_2 – ident: e_1_2_8_10_2 doi: 10.1109/ICVGIP.2008.85 – ident: e_1_2_8_4_2 doi: 10.1016/S0898-1221(00)00119-X – volume-title: YCoCg‐R: A Color Space with RGB Reversibility and Low Dynamic Range year: 2003 ident: e_1_2_8_24_2 – ident: e_1_2_8_18_2 – ident: e_1_2_8_23_2 doi: 10.1007/3DRes.04(2010)01 – volume-title: Real‐Time Texture Streaming & Decompression year: 2006 ident: e_1_2_8_36_2 – ident: e_1_2_8_26_2 doi: 10.1007/s00371-007-0163-2 – ident: e_1_2_8_34_2 doi: 10.1109/TPDS.2007.70716 – ident: e_1_2_8_9_2 doi: 10.1111/j.1467-8659.2008.01128.x – ident: e_1_2_8_13_2 doi: 10.1145/1536513.1536532 – ident: e_1_2_8_11_2 – ident: e_1_2_8_20_2 – ident: e_1_2_8_3_2 – ident: e_1_2_8_28_2 doi: 10.1108/02644400710729572 – ident: e_1_2_8_25_2 – ident: e_1_2_8_29_2 doi: 10.1145/218380.218437 – ident: e_1_2_8_14_2 – ident: e_1_2_8_22_2 – ident: e_1_2_8_7_2 – volume: 2 start-page: 489 year: 2008 ident: e_1_2_8_39_2 article-title: Large scale terrain compression and real‐time rendering based on wavelet transform publication-title: Proc. Computational Intelligence and Security (CIS) – volume-title: Real‐Time YCoCg‐DXT Compression year: 2007 ident: e_1_2_8_37_2 – volume-title: Histogram calculation in CUDA year: 2007 ident: e_1_2_8_27_2 – ident: e_1_2_8_2_2 doi: 10.1111/j.1467-8659.2006.00936.x – ident: e_1_2_8_6_2 doi: 10.1145/1229390.1229396 – ident: e_1_2_8_38_2 doi: 10.1109/TMM.2006.887994 – ident: e_1_2_8_15_2 doi: 10.1111/j.1467-8659.2008.01298.x
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Title	Interactive Editing of GigaSample Terrain Fields
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