Abstract
Compression is the process of reducing the size of an image. Reduction can be achieved through reducing the number of bits and encoding time. Encoding and decoding can be used to achieve compression and decompression. Encoding and decoding can be done through fractal image coding which uses the property of self-similarity between the blocks on the basis of affine transformations. Thus, our main goal is to analyze various techniques of fractal encoding for compressing the image. A systematic study of various fractal encoding techniques is done in this paper and based on the study a comparative analysis is presented.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Hassan, T.M., Wu, X.: An adaptive algorithm for improving the fractal image compression (FIC). J. Multimedia Acad. 6(6), 477–485 (2011)
Barnsley, M.F., Demko, S.: Iterated function systems and the global construction of fractals. In: Proceedings of Royal Society London. A, vol. 399, pp. 243–275 (1985)
Jacquin, A.E.: Image coding based on a fractal theory of iterated contractive image transformations. IEEE Trans. Image Process. 1, 18–30 (1992)
Jacobs, E.W., Fisher, Y., Boss, R.D.: Image compression: a study of the iterated transform method. IEEE Trans. Signal Process. 40, 251–263 (1992)
Fisher, Y.: Fractal image compression: in theory and application. Springer-Verlag, New York (1994)
Ramamurthi, B., Gersho, A.: Classified vector quantization of images: IEEE Trans. Commun. 34, 1105–1115 (1986)
Hu, L., Chen, Q.A., Zhang, D.: An image compression method based on fractal theory. In: The 8th International Conference on Computer Supported Cooperative Work in Design Proceedings, pp. 546–550 (2003)
Zhao, Y., Yuan, B.: Image compression using fractls and discrete cosine transform. Int. Lett. 30(6), 474–475 (1994)
Hamzaoui, R.: Decoding algorithm for fractal image compression. Electron. Lett. 32(14), 1273–1274 (1996)
Wang, J., Zheng, N.: A novel fractal image compression scheme with block classification and sorting based on Pearson’s correlation coefficient. IEEE Trans. Image Process. 22(9), 3690–3702 (2013)
Kodgule, U.B., Sonkamble, B.A.: Discrete wavelet transform based fractal image compression using parallel approach. Int. J. Comput. Appl. 122(16), 18–22 (2015)
Kapoor, A., Arora, K., Jain, A., Kapoor, G.P.: Stochastic image compression using fractals. Inf. Technol. Coding Comput.1–6 (2003)
Hamzaoui, R., Saupe, D., Hiller, M.: Fast code enhancement with local search for fractal image compression. In: 2000 International Conference on Image Processing, pp. 156–159 (2000)
Jacquin, A.E.: Image coding based on a fractal theory of iterated contractive image transformation. IEEE Trans. Image Process. 1(1), 18–30 (1992)
Hamzaoui, R., Saupe, D., Hiller, M.: Distortion minimisation with fast local search for fractal image compression. J. Vis. Comm. Image Represent. 2(4), 450–468 (2001)
Lee, C.K., Lee, W.K.: Fast fractal image block coding based on local variances. IEEE Trans. Image Process. 7(6), 888–891 (1998)
Gupta, R., Mehrotra, D., Tyagi, R.K.: Adaptive searchless fractal image compression in DCT domain. Imag. Sci. J. 1–7 (2016)
Revathy, K., Jayamhan, M.: Dynamic domain classification for fractal image compression. Comput. Vision. Pattern Recogn. 4(2), 95–102 (2012)
De Bono, J.P., Mcdowell, G.R.: The fractal micro mechanics of normal compression. Comput. Geotech. 78,11–24 (2016)
Mcdowell, G.R., de Bono, J.P.: On the micro mechanics of one-dimensional normal compression: Geotechnique. 63 895–908 (2013)
Mcdowell, G.R., de Bono, J.P., Yue, P., Yu, H-S.: Micro mechanics of isotropic normal compression. Géotechnique Lett. 3 166–172 (2013
McDowell, G.R., Yue, P., de Bono, J.P.: Micro mechanics of critical states for isotropically over consolidated sand. Powder Technol. 283, 440–446 (2015)
Sun, Y., Xu, R., Chen, L., Hu, X.: Image compression and encryption scheme using fractal dictionary and Julia set. IET Image Proc. 9, 173–183 (2015)
Prashanth, N., Singh, A.V.: Fractal image compression for hd images with noise using wavelet transforms. In: International Conference on Advances in Computing, Communications and Informatics, pp. 1194–1198 (2015)
Padmashree, S., Nagapadma, R.: Statistical analysis of objective measures using fractal image compression for medical images. In: IEEE International Conference on Signal and Image Processing Applications, pp. 563–568 (2015)
Xiaoqing, H., Qin, Z., Wenbo, L.: A new method for image retrieval based on analyzing fractal coding characters. J. Vis. Commun. Image Represent. 42–47 (2013)
Al-Hilo, E.A., George, L.E.: Study of fractal color image compression using YUV components. In: IEEE 36th International Conference on Computer Software and Applications, pp. 596–601 (2012)
Shih, C.W., Chu, H.C., Chen, Y.M., Wen, C.C.: The effectiveness of image features based on fractal image coding for image annotations. Expert Syst. Appl. 39, 12897–12904 (2012)
Lin, Y.L., Wu, M.S.: An edge property-based neighbourhood region search strategy for fractal image compression.Comput. Math. Appl. 62(1), 310–318(2011)
Duh, D.J., Jeng, J.H., Chen, S.Y.: Speed quality control for fractal image compression. Imag. Sci. J. 56, 79–90 (2008)
Truong, T.K., Kung, C.M., Jeng, J.H., Hsieh, M.L.: Fast fractal image compression using spatial correlation. Chaos, Solitons Fractals. 22, 1071–1076 (2004)
Muruganandhan, A., Banu, R.S.D.W.: Adaptive fractal image compression using PSO. Procedia Comput Sci. 2, 338–344 (2010
Troung, T.K., Jeng, J.H., Reed, I.S., Lee, P.C., Li, A.Q.: A fast encoding algorithm for fractal image compression using the DCT inner product. IEEE Trans. Image Process. 9, 529–535 (2000)
Woon, W.M., Ho, A.T., Yu, T., Tan, S.C., Yap, L.T.: Achieving high data compression of self-similar satellite images using fractal. In: IEEE 2000 International Symposium on Geo Science and Remote Sensing, vol. 2, pp. 609–6111 (2000)
Raman, V., Gupta, R.: JPEG multi-resolution decomposition of image compression using integer wavelets. Int. J. Comput. Appl. 95, 17–20 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Amin, S., Gupta, R., Mehrotra, D. (2018). Analytical Review on Image Compression Using Fractal Image Coding. In: Pant, M., Ray, K., Sharma, T., Rawat, S., Bandyopadhyay, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 584. Springer, Singapore. https://doi.org/10.1007/978-981-10-5699-4_30
Download citation
DOI: https://doi.org/10.1007/978-981-10-5699-4_30
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5698-7
Online ISBN: 978-981-10-5699-4
eBook Packages: EngineeringEngineering (R0)