Browse > Article
http://dx.doi.org/10.3837/tiis.2016.05.020

A Common Bitmap Block Truncation Coding for Color Images Based on Binary Ant Colony Optimization  

Li, Zhihong (Institute of Digital Multimedia and Communication, Taiyuan University of Science and Technology)
Jin, Qiang (Institute of Digital Multimedia and Communication, Taiyuan University of Science and Technology)
Chang, Chin-Chen (Department of Information Engineering and Computer Science, Feng Chia University)
Liu, Li (Institute of Digital Multimedia and Communication, Taiyuan University of Science and Technology)
Wang, Anhong (Institute of Digital Multimedia and Communication, Taiyuan University of Science and Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.10, no.5, 2016 , pp. 2326-2345 More about this Journal
Abstract
For the compression of color images, a common bitmap usually is generated to replace the three individual bitmaps that originate from block truncation coding (BTC) of the R, G and B channels. However, common bitmaps generated by some traditional schemes are not the best possible because they do not consider the minimized distortion of the entire color image. In this paper, we propose a near-optimized common bitmap scheme for BTC using Binary Ant Colony Optimization (BACO), producing a BACO-BTC scheme. First, the color image is compressed by the BTC algorithm to get three individual bitmaps, and three pairs of quantization values for the R, G, and B channels. Second, a near-optimized common bitmap is generated with minimized distortion of the entire color image based on the idea of BACO. Finally, the color image is reconstructed easily by the corresponding quantization values according to the common bitmap. The experimental results confirmed that reconstructed image of the proposed scheme has better visual quality and less computational complexity than the referenced schemes.
Keywords
Block truncation coding (BTC); binary ant colony optimization (BACO); common bitmap; image compression;
Citations & Related Records
연도 인용수 순위
  • Reference
1 C.K. Yang, J.C. Lin and W.H. Tsai, “Color image compression by moment-preserving and block truncation coding techniques,” IEEE Transactions on Communications, vol. 45, pp. 1513-1516, 1997. Article (CrossRef Link).   DOI
2 C.C. Chang and M.N. Wu, "An algorithm for color image compression based on common bit map block truncation coding," in Proc. of Joint Conf. Information Sciences, pp. 964-967, 2002. Article (CrossRef Link).
3 C.C. Chang, C.Y. Lin and Y. H. Fan, “Lossless data hiding for color images based on block truncation coding,” Pattern Recognition, vol. 41, no. 7, pp. 2347-2357, 2008. Article (CrossRef Link).   DOI
4 C.C. Chang, C.C. Lin, C.H. Lin and Y.H. Chen, “A novel secret image sharing scheme in color images using small shadow images,” Information Sciences, vol. 178, no. 11, pp. 2433-2447, 2008. Article (CrossRef Link).   DOI
5 M. Dorigo and G.D. Caro, "Ant colony optimization: a new meta-heuristic," in Proc. of Congress on Evolutionary Computation, Washington, DC, USA: IEEE Press, pp. 1470-1477, 1999. Article (CrossRef Link).
6 M. Dorigo and L.M. Gambardella, “Ant colony system: a cooperative learning approach to the traveling salesman problem,” IEEE Transactions on Evolutionary Computation, vol. 1, no. 1, pp. 53-66, 1997. Article (CrossRef Link).   DOI
7 M. Kong and P. Tian, "A binary ant colony optimization for the unconstrained function optimization problem," in Proc. of Int. Conf. on Computational Intelligence and Security, Part I, LNAI 3801, Springer, pp. 682-687, 2005. Article (CrossRef Link).
8 L. Hui, "An adaptive block truncation coding algorithm for image compression," in Proc. of IEEE Int. Acoustics, Speech, and Signal Processing, pp. 2233-2236, 1990. Article (CrossRef Link).
9 B.C. Dhara and B.Chanda, “Block truncation coding using pattern fitting,” Pattern Recognition, vol. 37, no. 11, pp. 2131-2139, 2004. Article (CrossRef Link).   DOI
10 M.D. Lema and O.R. Mitchell, “Absolute moment block truncation coding and applications to color images,” IEEE Transactions on Communications, vol. 32, no. 10, pp. 1148-1157, 1984. Article (CrossRef Link).   DOI
11 Y.C. Hu, “Predictive moment preserving block truncation coding for graylevel image compression,” Journal of Electronic Imaging, vol. 13, no. 4, pp. 871-877, 2004. Article (CrossRef Link).   DOI
12 J.M. Guo, H. Prasetyo and J.H. Chen, “Content-based image retrieval using features extracted from halftoning-based block truncation coding,” IEEE Transactions on Image Processing, vol. 24, no. 3, pp. 1010-1024, 2015. Article (CrossRef Link).   DOI
13 D. Ou, L. Ye and W. Sun, “User-friendly secret image sharing scheme with verification ability based on block truncation coding and error diffusion,” Signal Processing, vol. 29, pp. 46-60, 2015. Article (CrossRef Link).
14 N. Efrati, H. Licztin and H.B. Mitchell, “Classified block truncation coding-vector quantization: an edge sensitive image compression algorithm,” Signal Processing: Image Communication, vol. 3, pp. 275-283, 1991. Article (CrossRef Link).   DOI
15 I. Mor, Y. Swissa and H.B. Mitchell, “A fast nearly optimum equispaced 3-level block truncation coding,” Signal Processing: Image Communication, vol. 6, no. 5, pp. 397-404, 1994. Article (CrossRef Link).   DOI
16 Y. Wu and D.C. Coll, “Single bit-map block truncation coding of color images,” IEEE Journal on Selected Areas in Communications, vol. 10, no. 5, pp. 952-959, 1992. Article (CrossRef Link).   DOI
17 S.Y. Cui, Z.H. Wang, P.W. Tsai, C.C. Chang and S. Yue, "Single bitmap block truncation coding of color images using cat swarm optimization," Recent advances in information hiding and applications, Springer Berlin Heidelberg, pp. 119-138, 2013. Article (CrossRef Link).
18 E. J. Delp, and O. R. Mitchell, “Image compression using block truncation coding,” IEEE Transactions on Communications, vol. 27, no. 9, pp. 1335-1342, 1979. Article (CrossRef Link).   DOI
19 I.C. Chang, Y.C. Hu, W.L. Chen and C.C. Lo, “High capacity reversible data hiding scheme based on residual histogram shifting for block truncation coding,” Signal Processing, vol. 108, pp. 376-388, 2015. Article (CrossRef Link).   DOI
20 R.P. Jasmi, B. Perumal and M.P. Rajasekaran, "Comparison of image compression techniques using Huffman coding, DWT and fractal algorithm," in Proc. of 2015 Int. Conf. on Computer Communication and Informatics, pp. 8-10, 2015. Article (CrossRef Link).
21 C. Qin, C.C. Chang, G. Horng, Y.H. Huang and Y.C. Chen, “Reversible data embedding for vector quantization compressed images using search-order coding and index parity matching,” Security and Communication Networks, vol. 8, no. 6, pp. 899-906, 2015. Article (CrossRef Link).   DOI
22 R. Bose and S. Pathak, “A novel compression and encryption scheme using variable model arithmetic coding and coupled chaotic system,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 53, no. 4, pp. 848-857, 2006. Article (CrossRef Link).   DOI
23 P. Slusarczyk and R. Baran, “Piecewise-linear subband coding scheme for fast image decomposition,” Multimedia Tools and Applications, pp. 1-18, 2014. Article (CrossRef Link).
24 B. Li and Q. Meng, "An improved SPIHT wavelet transform in the underwater acoustic image compression," in Proc. of Int. Conf. on Measurement, Information and Control (ICMIC), pp. 1315-1318, 2013. Article (CrossRef Link).
25 F. Daraee and S. Mozaffari, “Watermarking in binary document images using fractal codes,” Pattern Recognition Letters, vol. 35, pp. 120-129, 2014. Article (CrossRef Link).   DOI
26 Y. Yang, Q. Chen and Y. Wan, “A fast near-optimum block truncation coding method using a truncated K-means algorithm and inter-block correlation,” International Journal of Electronics and Communications (AEU), vol. 65, no. 6, pp. 576-581, 2011. Article (CrossRef Link).   DOI
27 W. Xiong, L. Wang and C. Yan, "Binary ant colony evolutionary algorithm," in Proc. of Int. Conf. on Intelligent Computing, pp. 10-20, 2005. Article (CrossRef Link).