Abstract
We have developed a new stochastic image rendering method for the compression, description and segmentation of images. This paintbrush-like image transformation is based on a random searching to insert brush-strokes into a generated image at decreasing scale of brush-sizes, without predefined models or interaction. We introduced a sequential multiscale image decomposition method, based on simulated rectangular-shaped paintbrush strokes. The resulting images look like good-quality paintings with well-defined contours, at an acceptable distortion compared to the original image. The image can be described with the parameters of the consecutive paintbrush strokes, resulting in a parameter-series that can be used for compression. The painting process can be applied for image representation, segmentation and contour detection. Our original method is based on stochastic exhaustive searching which takes a long time of convergence. In this paper we propose a modified algorithm of speed up of about 2x where the faster convergence is supported by a dynamic Metropolis Hastings rule.
This work was partly done during the stay of T. Szirányi at Ariana project, INRIA, 2000
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References
Y. Fisher. (ed.), Fractal Image Compression, Springer Verlag (1994)
S. Geman, D. Geman, “Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images, ” IEEE Tr. PAMI, Vol. 6, pp. 721–741 (1984)
P.E. Haeberli, “Paint by numbers: Abstract image representations”, Computer Graphics, (Proc. SIGGRAPH’ 1990), V. 24, pp. 207–214, (1990)
H. H.S. Ip, H. T. F. Wong, “Generation of Brush Written Characters with fractal Characteristics from True-type Fonts”, ICCPOL, 17th Int. Conf. on Computer Processing of Oriental Languages, pp. 156–161, Hong Kong (1997)
H. H S Ip, H. T F Wong, “Calligraphic Character Synthesis using Brush Model”, CGI’97, Computer Graphics International conference, pp. 13–21, Hasselt-Diepenbeek, Belgium, June 23–27 (1997)
T. Lindeberg, B. M. Haar Romeny, “Linear scale-space I-II”, Geometry-Driven Diff. In Computer Vision, Kluwer Academic Publishers, pp. 1–72 (1992)
P. Litwinowicz, ‘Processing Images and Video for An Impressionist Effect’, Computer Graphics, (Proc.SIGGRAPH’1997), pp. 407–414 (1997)
R. Neff, A. Zakhor, “Very low bit-rate video coding based on matching pursuits”, IEEE Tr. CAS VT, Vol. 7, pp. 158–171 (1997)
Ch. P. Robert, G. Casella, “Monte Carlo Statistical Methods“, Springer Text in Statistics (1999)
T. Szirányi, I. Kopilovic, B. P. Tóth, “Anisotropic Diffusion as a Preprocessing Step for Efficient Image Compression”, Proc. of the 14 th ICPR Brisbane, IAPR&IEEE, Australia, pp. 1565–1567, August 16–20 (1998)
T. Szirányi, Z. Toth, “Random Paintbrush Transformation”, 15 th ICPR, Barcelona, IAPR&IEEE, V. 3, pp. 155–158 (2000)
T. Szirányi, J. Zerubia, “Markov Random Field Image Segmentation using Cellular Neural Network”, IEEE CAS I., Vol. 44, pp. 86–89 (1997)
P. Teo, D. Heeger, “Perceptual Image Distortion”, First IEEE Int.Conf. Image Proc., Vol. 2, pp. 982–986 (1994)
S.C. Zhu, D. Mumford, “Prior Learning and Gibbs Reaction-Diffusion“, IEEE Tr. PAMI, Vol. 19, pp. 1236–1250 (1997)
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Szirányi, T., Tóth, Z. (2001). Optimization of Paintbrush Rendering of Images by Dynamic MCMC Methods. In: Figueiredo, M., Zerubia, J., Jain, A.K. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2001. Lecture Notes in Computer Science, vol 2134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44745-8_14
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DOI: https://doi.org/10.1007/3-540-44745-8_14
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