Block sampling based method and apparatus for texture synthesis

Computer graphics processing and selective visual display system – Computer graphics processing – Attributes

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Reexamination Certificate

active

07023447

ABSTRACT:
A novel multi-resolution block sampling based texture analysis/synthesis algorithm. A reference texture is assumed to be sample from a probability function. The synthesis of a similar, but distinctive, synthetic texture is handled in a process and by an apparatus that first estimates and then resamples the probability function. In order to achieve good and fast estimation of the probability function for a reference texture and in order to retain the texel structural information during the synthesis, a novel concept of block sampling and a corresponding novel texture synthesis scheme based on multi-resolution block sampling is employed. As a result of this novel approach, the computational complexity of the present invention is much lower than that of other approaches to the problem. In addition, for textures that exhibit a high degree of directionality, a process, which integrates estimation of dominant texture direction and the synthesis algorithm is employed to handle directional textures. The dominant direction is used to orient and then control the synthesis process so as to preserve the dominant reference image direction.

REFERENCES:
patent: 5544292 (1996-08-01), Winser
patent: 5641596 (1997-06-01), Gray et al.
patent: 5872867 (1999-02-01), Bergen
patent: 6643406 (2003-11-01), Hajjahmad et al.
patent: 2002/0006229 (2002-01-01), Chao et al.
patent: 2003/0076334 (2003-04-01), Dumitras et al.
“Texture mixing and texture movie synthesis using statistical learning” Bar-Joseph, Z.; El-Yaniv, R.; Lischinski, D.; Werman, M.; Visualization and Computer Graphics, IEEE Transactions on , vol.: 7 , Issue: 2 , Apr.-Jun. 2001 pp.: 120-135.
“An Implementation of Heeger and Bergen's Texture Analysis/Synthesis Algorithm” Thomas F. El-Maraghi Department of Computer Science;University of Toronto;Sep. 2, 1997.
“Texture Mixing and Texture Movie Synthesis using Statistical Learning” Bar-Joseph, Z.; El-Yaniv, R.; Lischinski, D.; Werman, M.; Visualization and Computer Graphics, IEEE Transactions on , vol.: 7 , Issue: 2 , Apr.-Jun. 2001.
B. Julesz, “Visual pattern discrimination”, IRE Trans. of Information Theory IT-8. System, Man, and Cybernetics, p. 84-92, 1962.
R.M. Haralick, K. Shanmugan, and I. Dinstein. “Textural Features for Image Classification”, IEEE Trans. System, Man, and Cybernetics, vol. 8, pp. 610-621, Nov. 1973.
G.R. Cross and A.K. Jain, “Markov random field texture models”, IEEE Trans. On Pattern Analysis and Machine Intell., vol. 5, No. 1, pp. 25-39, Jan. 1983.
H. Derin and H. Elliott, “Modeling and Segmentation of Noisy and Textured Images Using Gibbs Random Fields”. IEEE Trans. Pattern Analysis and Machine Intell., vol. 9, No. 1, pp. 39-55, Jan. 1987.
M. Bastiaans, “Gabor's expansion of a signal into Gaussian elementray signal”, IEEE, vol. 68, p. 538-539, 1980.
S.G. Mallat, “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation”, IEEE Trans. Pattern Anal. and Machine Intell., vol. 11, pp. 674-693, Jul. 1989.
D. J. Heeger, J.R. Bergen, “Pyramid-based texture analysis/synthesis”, ACM Proceedings of SIGGRAPH, pp. 229-238, Aug. 1995.
S.C. Zhu, Y.N. Wu and D. Mumford, “Filters, random fields and maximum entropy (FRAME): Towards a Unified Theory for Texture Modeling”, International Journal of Computer Vision, vol. 27, No. 2, pp. 107-126, Jun. 1996.
J.S. De Bonet, “Multi-resolution sampling procedure for analysis and synthesis of texture image”, ACM Proceedings of SIGGRAPH, pp. 361-368, Aug. 1997.
E.P. Simoncelli, J. Portilla. “Texture,Characterization via Joint Statistics of Wavelet Coefficient Magnitudes”, IEEE Inter. Conf. on Image Processing), vol. 1, pp. 62-66, Oct. 1998.
A. Efros and T. Leung, “Testure synthesis by non-parametric sampling”, IEEE Int. Conf. on Computer Vission, vol. 2, pp. 1033-1038, Sep. 1999.
Ying-Qing Xu, Baining Guo, and Harry Shum. “Chaos Mosaic: Fast and Memory Efficient Texture Synthesis” Microsoft Research Report, Apr. 2000.
L.Y. Wei and M. Levoy, “Fast texture synthesis using tree-structured vector quantization”, ACM Proceedings of SIGGRAPH, 2000.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Block sampling based method and apparatus for texture synthesis does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Block sampling based method and apparatus for texture synthesis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Block sampling based method and apparatus for texture synthesis will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3534236

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.