Abstract
2D texture data represent one of the main data sources in 3D graphics, requiring large amounts of memory and bandwidth. Texture compression is of critical importance in this context to cope with these bottlenecks. To improve upon the available supported texture compression systems, several transform-based solutions have been proposed. These solutions, however, are not suitable for real-time texture sampling or provide insufficient image quality at medium to low rates. We propose a new scalable texture codec based on the 2D wavelet transform suitable for real-time rendering and filtering, using a new subband coding technique. The codec offers superior compression performance compared to the state-of-the-art, resolution scalability coupled with a wide variety of quality versus rate trade-offs as well as complexity scalability supported by the use of different wavelet filters.

































Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Notes
We can do this by setting the OpenGL texture coordinate wrapping mode to GL_MIRRORED_REPEAT.
References
Iourcha, K. I., Nayak, K. S., Hong, Z.: Fixed-rate block-based image compression with inferred pixel values. US Patent 6,658,146 (2003)
Microsoft, texture block compression in direct3D 11. https://msdn.microsoft.com/en-us/library/windows/desktop/hh308955. Accessed 20 Jan 2016
Delp, E., Mitchell, O.: Image compression using block truncation coding. IEEE Trans. Commun. 27(9), 1335–1342 (1979)
Nystad, J., Lassen, A., Pomianowski, A., Ellis, S., Olson, T.: Adaptive scalable texture compression. In: Dachsbacher, C., Munkberg, J., Pantaleoni, J. (eds.) High performance graphics, pp. 105–114, Eurographics Association (2012)
Beers, A. C., Agrawala, M., Chaddha, N.: Rendering from compressed textures. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’96, New York, pp. 373–378, ACM (1996)
Kilgard, M. J., Brown, P., Zhang, Y., Barsi, A.: LATC OpenGL extension. https://www.opengl.org/registry/specs/EXT/texture/compression/latc.txt,2009. Accessed 20 Jan 2016
Pereberin, et al. A. V.: Hierarchical approach for texture compression. In: Proceedings of graphiCon n++99, pp. 195–199 (1999)
Fenney, S.: Texture compression using low-frequency signal modulation. In: Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Conference on Graphics Hardware, HWWS ’03, (Aire-la-Ville, Switzerland), pp. 84–91, Eurographics Association (2003)
Diverdi, S., Candussi, N., Höllerer, T.: Real-Time Rendering with Wavelet-Compressed Multi-Dimensional Textures on the GPU. University of California, Santa Barbara (2005)
Sun, C.-H., Tsao, Y.-M., Chien, S.-Y.: High-quality mipmapping texture compression with alpha maps for graphics processing units. IEEE Trans. Multimed. 11(4), 589–599 (2009)
Grund, N., Menzel, N., Klein, R.: High-quality wavelet compressed textures for real-time rendering. WSCG Short Pap. 18, 207–212 (2010)
Hollemeersch, C.-F., Pieters, B., Lambert, P., Van de Walle, R.: A new approach to combine texture compression and filtering. Vis. Comput. 28(4), 371–385 (2012)
Mavridis, P., Papaioannou, G.: Texture Compression Using Wavelet Decomposition. In: Computer graphics forum, vol. 31, pp. 2107–2116, Wiley Online Library (2012)
Tenllado, C., Lario, R., Prieto, M., Tirado, F.: The 2d discrete wavelet transform on programmable graphics hardware. In: IASTED Visualization, Imaging and Image Processing Conference (2004)
Wong, T.-T., Leung, C.-S., Heng, P.-A., Wang, J.: Discrete wavelet transform on consumer-level graphics hardware. IEEE Trans. Multimed. 9(3), 668–673 (2007)
Tenllado, C., Setoain, J., Prieto, M., Piñuel, L., Tirado, F.: Parallel implementation of the 2D discrete wavelet transform on graphics processing units: filter bank versus lifting. IEEE Trans. Parallel Distrib. Syst. 19(3), 299–310 (2008)
van der Laan, W.J., Jalba, A.C., Roerdink, J.: Accelerating wavelet lifting on graphics hardware using CUDA. IEEE Trans. Parallel Distrib. Syst. 22(1), 132–146 (2011)
Treib, M., Reichl, F., Auer, S., Westermann, R.: Interactive editing of gigasample terrain fields. In: Computer Graphics Forum, vol. 31, pp. 383–392, Wiley Online Library (2012)
Malvar, H., Sullivan, G.: YCoCg-R: a color space with RGB reversibility and low dynamic range. ISO/IEC JTC1/SC29/WG11 and ITU (2003)
Mallat, S.G.: A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 11(7), 674–693 (1989)
Cohen, A., Daubechies, I., Feauveau, J.-C.: Biorthogonal bases of compactly supported wavelets. Commun. Pure Appl. Math. 45(5), 485–560 (1992)
Mallat, S.: A Wavelet Tour of Signal Processing Academic, Vol. 16. New York (1998)
Andries, B., Lemeire, J., Munteanu, A.: Optimized quantization of wavelet subbands for high quality real-time texture compression. In: IEEE International Conference on Image Processing 2014, Paris, France (2014)
Alecu, A., Munteanu, A., Schelkens, P., Cornelis, J., Dewitte, S.: Wavelet-based fixed and embedded L-infinite-constrained image coding. J. Electr. Imag. 12(3), 522–538 (2003)
Alecu, A., Munteanu, A., Cornelis, J., Schelkens, P.: Wavelet-based scalable L-infinity-oriented compression. IEEE Trans. Image Process. 15(9), 2499–2512 (2006)
Nvidia Texture Tools. https://github.com/castano/nvidia-texture-tools (2010). Accessed 20 Jan 2016
ASTC encoder. https://github.com/ARM-software/astc-encoder (2015). Accessed 20 Jan 2016
Kodak image set. http://r0k.us/graphics/kodak/. Accessed 10 Aug 2015
Bjontegaard, G.: Calcuation of average PSNR differences between RD-curves. Doc. VCEG-M33 ITU-T Q6/16, Austin, 2–4 April (2001)
Acknowledgments
The Kodim test images used in this paper are courtesy of KODAK [28]. This work was funded by the Agency for Innovation by Science and Technology in Flanders (IWT) through bursary SB-536, by the iMinds institute through the ICON project BAHAMAS and by the Research Foundation - Flanders (FWO).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Andries, B., Lemeire, J. & Munteanu, A. Scalable texture compression using the wavelet transform. Vis Comput 33, 1121–1139 (2017). https://doi.org/10.1007/s00371-016-1269-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00371-016-1269-1