A proposition of mobile fractal image decompression

Nikiel, S.

International Journal of Applied Mathematics and Computer Science, Tome 17 (2007) no. 1, pp. 129-136.

Résumé

Multimedia are becoming one of the most important elements of the user interface with regard to the acceptance of modern mobile devices. The multimodal content that is delivered and available for a wide range of mobile telephony terminals is indispensable to bind users to a system and its services. Currently available mobile devices are equipped with multimedia capabilities and decent processing power and storage area. The most crucial factors are then the bandwidth and costs of media transfer. This is particularly visible in mobile gaming, where textures represent the bulk of binary data to be acquired from the content provider. Image textures have traditionally added visual realism to computer graphics. The realism increases with the resolution of textures. This represents a challenge to the limited bandwidth of mobile-oriented systems. The challenge is even more obvious in mobile gaming, where single image depicts a collection of shots or animation cycles for sprites and a backdrop scenery. In order to increase the efficiency of image and image texture transfer, a fractal based compression scheme is proposed. The main idea is to use an asymmetric server-client architecture. The resource demanding compression process is performed on the server side while the client part decompresses highly packed image data. The method offers a very high compression ratio for pictures representing image textures for natural scenes. It aims to minimize the transmission bandwidth that should speed up the downloading process and minimize the cost and time of data transfer. The paper focuses on the implementation of fractal decompression schemes suitable for most mobile devices, and opens a discussion on fractal image models for limited resource applications.

Détail

Keywords: fractals, image processing, fractal image compression, mobile media, texture mapping
Mots-clés : fraktale, przetwarzanie obrazu, fraktalna kompresja obrazu, mobilne media, mapowanie tekstur

Bibliographie

[1] Atkinson S.,Machin A., GrafM., Hageland M., Nashi A., Taylor R., Ayers D., Ray B. and Wiggers Ch. (2001): Professional Java Mobile Programming. - Chicago: Wrox Press Ltd., (R. Ashri, Ed.).

[2] Baharav Z., Malah D. and Karnin E. (1993): Hierarchical interpretation of fractal image coding and its application to fast decoding. - Proc. Int. Conf. Digital Signal Processing, Levkosia, Cyprus, pp. 190-195.

[3] Beers A., Agrawala M. and Chadda N. (1996): Rendering for compressed textures. - Proc. Int. Conf. Computer Graphics and Interactive Techniques, SIGGRAPH, New Orleans, USA, pp. 373-378.

[4] Bury S. (2004): Fractal imaging on mobile phones. - M.Sc. thesis, University of Zielona Góra, Poland (in Polish).

[5] Chen C. and Lee C. (2002): A JPEG-like texture compression with adaptive quantization for 3D graphics application. - The Visual Computer, Vol. 18, No. 1, pp. 29-40.

[6] Cisar G. (1996): On Entropy Coding Fisher's Fractal Quad Tree Code. - Tech. Rep., Institut fur Informatik, University of Freiburg, Germany.

[7] Condissi N., DiVerdi T. and Hoeller T. (2005): Real-time rendering with wavelet-compressed multi-dimensional textures on the GPU. - Tech. Rep. 2005.05, Comput. Sci.,University of California, Santa Barbara.

[8] Delp E. and Mitchell O. (1979): Image compression using block truncation coding.-IEEE Trans. Commun., Vol. 2, No. 9, pp. 1335-1342.

[9] Fisher Y. (1995): Fractal Image Compression: Theory and Application. - London: Springer.

[10] Ghulam M, Falai C. and Zhangijn H. (2004): Ternary wavelets and their applications to signal compression. - Int. J. Appl. Math. Comput. Sci., Vol. 14, No. 2, pp. 233-240.

[11] Knittel G., Shilling A., Kugler A. and StrasserW. (1996): Hardware for superior texture performance.-Comput. Graphics, Vol. 20, No. 4, pp. 475-481.

[12] Kwon Y., Park I. and Kyung Ch. (2000): Pyramid texture compression and decompression using interpolative vector quantization.-Pro. Int. Conf. Image Processing, Vancouver, Canada, Vol. 2., pp. 89-106.

[13] Malah D. and Sutskover I. (1999): Hierarchical Fast Decoding of Fractal Image Representation Using Quadtree Partitioning. - Technion, Israel: I.I.T.

[14] Microsoft (1997): Escalante hardware overview - Talisman. - Graph. Multimedia Syst., Vol. 18, No. 1, pp. 89-106.

[15] Nikiel S. and Moczulski M. (2006): Image acquisition and segmentation on mobile devices.-Proc. Nat. Conf. Measurement Systems, SP, Łagów, Poland, pp. 69-70, (in Polish).

[16] Pazio M. and Cisowski K. (2005): Application of colour image segmentation for localization and extraction text from images. - Proc. Conf. Poznań Telecommunication Workshops, PWT, Poznań, Poland pp. 134-137.

[17] Perebrin A. (1999): Hierarchical approach to texture compression. - Proc. Conf. GRAPHICON, San Francisco, USA, pp. 195-199.

[18] Skarbek W. (1998): Rough sets and current trends in computing - Proc. 1st Int. Conf. Rough Sets and Current Trends in Computing, RSCTC,Warsaw, Poland, pp. 441-453.

[19] Stachera J. and Rokita P. (2006): GPU-based hierarchical texture decompression. - Proc. Int. Conf. Eurographics, Vienna, Austria, (on DVD).

[20] Stachera J. and Nikiel S. (2004): Fractal image compression for efficient texture mapping. - Proc. Int. Conf. Winter School on Computer Graphics, WSCG Plzen, Czech Republic, pp. 169-172.