Research Article
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Year 2025, Early View, 1 - 1
https://doi.org/10.35378/gujs.1425702

Abstract

References

  • [1] Hutchinson, J.E., “Fractals and self similarity”, Indiana University Mathematics Journal, 30(5): 713-747, (1981).
  • [2] Barnsley, M.F., “Fractals Everywhere”, Dover Publications, Inc: Mineola, New York, USA, (2012).
  • [3] Barnsley, M.F., Sloan, A.D., “A better way to compress images”, Byte 13(1): 215-223, (1988).
  • [4] Aslan, İ., Gökçer Ellidokuz, T.Y., “Approximation by N-dimensional max-product and max-min kind discrete operators with applications”, Filomat, 38(5): 1825-1845, (2024).
  • [5] Çelik, D., Deniz, A., Özdemir, Y., “Graph-Directed Fractal Image Compression”, Eskişehir Technical University Journal of Science and Technology B- Theoretical Sciences, 10(1): 1-10, (2022).
  • [6] Gökçer, T.Y., Aslan, İ., “Approximation by Kantorovich-type max-min operators and its applications”, Applied Mathematics and Computation 423: 127011, (2022).
  • [7] Menassel, R., “Optimization of fractal image compression”, Fractal Analysis-Selected Examples. IntechOpen, (2020).
  • [8] Nandi, U., “Fractal image compression using a fast affine transform and hierarchical classification scheme”, The Visual Computer, 38(11): 3867-3880, (2022).
  • [9] Jacquin, A.E., “Image coding based on a fractal theory of iterated contractive image transformations”, IEEE Transactions on image processing, 1(1): 18-30, (1992).
  • [10] Fischer, Y., “Fractal Image Compression Theory and Application”, Springer, New York, (1994).
  • [11] Nandi, U., Fractal image compression with adaptive quardtree partitioning and non-linear affine Map, Multimedia Tools and Applications, 79(35): 26345-26368, (2020).
  • [12] Nandi, U., Mandal, J. K., Efficiency and capability of fractal image compression with adaptive quadtree partitioning, The International Journal of Multimedia & Its Applications, 5(4): 53, (2013).
  • [13] Xu, C., Xie, D., Guo, H., He, J., Chen, M., “Optimization Method for Fractal Image Compression Based on Self-similarity Evaluation and Gradient Bisection Algorithm”, In International Conference on Intelligent Computing (pp. 218-233). Singapore: Springer Nature, Singapore, (2024).
  • [14] Aslan, N., Aslan, İ., “Approximation to the classical fractals by using non-affine contraction mappings”, Portugaliae Mathematica, 79: 45–60, (2022).

Fractal Image Decompression via Non-affine Contractions

Year 2025, Early View, 1 - 1
https://doi.org/10.35378/gujs.1425702

Abstract

In this study, considering the well-known fractal image compression, we introduce the image decompression method through non-affine contraction mappings. To achieve this, we convert affine contraction mappings into non-affine contraction mappings using Lipschitz continuous functions, subject to certain assumptions. Our expectation is to obtain decompressed images of superior quality compared to the classical fractal image compression method. We also apply our method for audio decompression. At the end, we illustrate the proposed method with some examples.

References

  • [1] Hutchinson, J.E., “Fractals and self similarity”, Indiana University Mathematics Journal, 30(5): 713-747, (1981).
  • [2] Barnsley, M.F., “Fractals Everywhere”, Dover Publications, Inc: Mineola, New York, USA, (2012).
  • [3] Barnsley, M.F., Sloan, A.D., “A better way to compress images”, Byte 13(1): 215-223, (1988).
  • [4] Aslan, İ., Gökçer Ellidokuz, T.Y., “Approximation by N-dimensional max-product and max-min kind discrete operators with applications”, Filomat, 38(5): 1825-1845, (2024).
  • [5] Çelik, D., Deniz, A., Özdemir, Y., “Graph-Directed Fractal Image Compression”, Eskişehir Technical University Journal of Science and Technology B- Theoretical Sciences, 10(1): 1-10, (2022).
  • [6] Gökçer, T.Y., Aslan, İ., “Approximation by Kantorovich-type max-min operators and its applications”, Applied Mathematics and Computation 423: 127011, (2022).
  • [7] Menassel, R., “Optimization of fractal image compression”, Fractal Analysis-Selected Examples. IntechOpen, (2020).
  • [8] Nandi, U., “Fractal image compression using a fast affine transform and hierarchical classification scheme”, The Visual Computer, 38(11): 3867-3880, (2022).
  • [9] Jacquin, A.E., “Image coding based on a fractal theory of iterated contractive image transformations”, IEEE Transactions on image processing, 1(1): 18-30, (1992).
  • [10] Fischer, Y., “Fractal Image Compression Theory and Application”, Springer, New York, (1994).
  • [11] Nandi, U., Fractal image compression with adaptive quardtree partitioning and non-linear affine Map, Multimedia Tools and Applications, 79(35): 26345-26368, (2020).
  • [12] Nandi, U., Mandal, J. K., Efficiency and capability of fractal image compression with adaptive quadtree partitioning, The International Journal of Multimedia & Its Applications, 5(4): 53, (2013).
  • [13] Xu, C., Xie, D., Guo, H., He, J., Chen, M., “Optimization Method for Fractal Image Compression Based on Self-similarity Evaluation and Gradient Bisection Algorithm”, In International Conference on Intelligent Computing (pp. 218-233). Singapore: Springer Nature, Singapore, (2024).
  • [14] Aslan, N., Aslan, İ., “Approximation to the classical fractals by using non-affine contraction mappings”, Portugaliae Mathematica, 79: 45–60, (2022).
There are 14 citations in total.

Details

Primary Language English
Subjects Image Processing, Approximation Theory and Asymptotic Methods, Applied Mathematics (Other)
Journal Section Research Article
Authors

Nisa Aslan 0000-0002-2103-0511

İsmail Aslan 0000-0001-9753-6757

Early Pub Date December 11, 2024
Publication Date
Submission Date January 25, 2024
Acceptance Date November 8, 2024
Published in Issue Year 2025 Early View

Cite

APA Aslan, N., & Aslan, İ. (2024). Fractal Image Decompression via Non-affine Contractions. Gazi University Journal of Science1-1. https://doi.org/10.35378/gujs.1425702
AMA Aslan N, Aslan İ. Fractal Image Decompression via Non-affine Contractions. Gazi University Journal of Science. Published online December 1, 2024:1-1. doi:10.35378/gujs.1425702
Chicago Aslan, Nisa, and İsmail Aslan. “Fractal Image Decompression via Non-Affine Contractions”. Gazi University Journal of Science, December (December 2024), 1-1. https://doi.org/10.35378/gujs.1425702.
EndNote Aslan N, Aslan İ (December 1, 2024) Fractal Image Decompression via Non-affine Contractions. Gazi University Journal of Science 1–1.
IEEE N. Aslan and İ. Aslan, “Fractal Image Decompression via Non-affine Contractions”, Gazi University Journal of Science, pp. 1–1, December 2024, doi: 10.35378/gujs.1425702.
ISNAD Aslan, Nisa - Aslan, İsmail. “Fractal Image Decompression via Non-Affine Contractions”. Gazi University Journal of Science. December 2024. 1-1. https://doi.org/10.35378/gujs.1425702.
JAMA Aslan N, Aslan İ. Fractal Image Decompression via Non-affine Contractions. Gazi University Journal of Science. 2024;:1–1.
MLA Aslan, Nisa and İsmail Aslan. “Fractal Image Decompression via Non-Affine Contractions”. Gazi University Journal of Science, 2024, pp. 1-1, doi:10.35378/gujs.1425702.
Vancouver Aslan N, Aslan İ. Fractal Image Decompression via Non-affine Contractions. Gazi University Journal of Science. 2024:1-.