Summary
This chapter proposes a novel color image compression technique based on Block Truncation Coding (BTC) using Cat Swarm Optimization (CSO). The original BTC method compresses a block of a grayscale image into a bitmap and a pair of quantization numbers. For a color image, which is encoded using R, G, and B channels, the BTC method enhances the compression rate using a common bitmap instead of three naturally formed bitmaps. However, it is difficult to find an efficient common bitmap due to its complexity. The CSO algorithm is generated by modeling the behaviors of cats, which show better performance in achieving the goal of finding best solution than other optimization algorithms. In this chapter, we adopt Cat Swarm Optimization (CSO) to search for a near optimal solution for this problem. The experimental results indicate that the proposed method could improve the decompressed BTC color image quality by obtaining a near optimal solution of the common bit map.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Delp, E.J., Mitchell, O.R.: Image compression using block truncation coding. IEEE Trans. Communications 27, 1335–1342 (1979)
Rao, Y.V.R., Eswama, C.: A new algorithm for BTC image bit plane coding. IEEE Trans. Communications 43, 2010–2011 (1995)
Wu, Y., Coll, D.C.: Single bit-map block truncation coding of color images. IEEE Journal on Selected Areas in Communications 10, 952–959 (1992)
Kurita, T., Otsu, N.: A method of block truncation coding of color image compression. IEEE Trans. Communications 41, 1270–1274 (1993)
Tai, S.C., Lin, Y.C., Lin, J.F.: Single bit-map block truncation coding of color images using a Hopfield neural network. Information Sciences 103, 211–228 (1997)
Tai, S.C., Chen, W.J., Cheng, P.J.: Genetic algorithm for single bitmap absolute moment block truncation coding of color images. Optical Engineering 37, 2483–2489 (1998)
Chang, C.C., Wu, M.N.: An algorithm for color image compression based on common bit map block. In: Proc. Second Int’l. Workshop on Intelligent Multimedia Computing and Networking, pp. 964–967 (2002)
Chu, S.C., Tsai, P.W.: Computational intelligence based on the behavior of cats. International Journal of Innovative Computing, Information and Control 3, 163–173 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Cui, SY., Wang, ZH., Tsai, PW., Chang, CC., Yue, S. (2013). Single Bitmap Block Truncation Coding of Color Images Using Cat Swarm Optimization. In: Pan, JS., Huang, HC., Jain, L., Zhao, Y. (eds) Recent Advances in Information Hiding and Applications. Intelligent Systems Reference Library, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28580-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-28580-6_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28579-0
Online ISBN: 978-3-642-28580-6
eBook Packages: EngineeringEngineering (R0)