Abstract
This paper presents the comparative review of wavelet encoder and fractal image compression (FIC) based on DWT. Wavelet transforms, and FIC are popularly used as the domain for image compression. Encoder designed in the spatial domain cannot exploit the redundancy present in the natural image efficiently. In this paper, the image is encoded using conventional fractal encoding algorithm in both the transforms. Performance of both the encoder compared using compression ratio, encoding time and PSNR. Raw images of size 512 × 512 used to carry the experiment in Matlab2013a. A quick review is arranged in a tabular manner in Sect. 4.
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
References
Barnsley MF (2014) Fractals everywhere. Academic Press
Barnsley MF, Sloan AD (1988) A better way to compress images. Byte 13(1):215–223
Jacquin AE (1992) Image coding based on a fractal theory of iterated contractive image transformations. IEEE Trans Image Process 1(1):18–30
Pentland A, Horowitz B (1991) A practical approach to fractal-based image compression. In: Data compression conference, 1991. DCC’91. IEEE
Davis G (1995) Self-quantized wavelet subtrees: a wavelet-based theory for fractal image compression. In: Data compression conference, 1995. DCC’95. Proceedings. IEEE
Andreopoulos I, Karayianris YA, Stouruaitis T (2000) A hybrid image compression algorithm based on fractal coding and wavelet transform. In: The 2000 IEEE international symposium on circuits and systems, 2000. Proceedings. ISCAS 2000 Geneva, vol 3. IEEE
Li J, Kuo C-CJ (1999) Image compression with a hybrid wavelet-fractal coder. IEEE Trans Image Process 8(6):868–874
Wu M (2000) A new fractal zerotree coding for wavelet image. J Electron 17(3):254–260
Xie X, Ma ZM (2000) Fractal predictive image coding based on zerotrees of wavelet coefficients. J Image Graphics A 5:920–924
Kim SH, Jang IH, Kim NC (2002) Image coding using wavelet-based fractal approximation. IEICE Trans Inf Syst 85(10):1723–1726
Xie YH, Fu DS, Ren W (2003) A fractal image coding algorithm research based on wavelet transformation. J Image Graphics 7(8):839–842
Wang DF, Jiang W (2005) Fractal image coding combined with wavelet subtree. Syst Eng Electron 27(6):1120–1122
Iano Y, da Silva FS, Mendes Cruz AL (2006) A fast and efficient hybrid fractal-wavelet image coder. IEEE Trans Image Process 15(1):98–105
Song C-L et al (2007) A novel fractal wavelet image compression approach. J China Univ Min Technol 17(1):121–125
Moreno J, Otazu X (2011) Image compression algorithm based on Hilbert scanning of embedded quadtrees: an introduction of the hi-set coder. In: 2011 IEEE international conference on multimedia and expo (ICME). IEEE
Zhang Y, Wang X (2012) Fractal compression coding based on wavelet transform with diamond search. Nonlinear Anal Real World Appl 13(1):106–112
Wu M-S (2014) Genetic algorithm based on discrete wavelet transformation for fractal image compression. J Vis Commun Image Represent 25(8):1835–1841
Wang X-Y, Zhang D-D (2014) Discrete wavelet transform-based simple range classification strategies for fractal image coding. Nonlinear Dyn 75(3):439–448
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Gupta, R., Mehrotra, D., Tyagi, R.K. (2019). Comparative Analysis of Wavelet Encoder and Hybrid Wavelet-Based Fractal Encoder for Image. In: Kumar, M., Pandey, R., Kumar, V. (eds) Advances in Interdisciplinary Engineering . Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-6577-5_34
Download citation
DOI: https://doi.org/10.1007/978-981-13-6577-5_34
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6576-8
Online ISBN: 978-981-13-6577-5
eBook Packages: EngineeringEngineering (R0)