Abstract
With images replacing textual and audio in most technologies, the volume of image data used in everyday life is very large. It is thus important to make the image file sizes smaller, both for storage and file transfer. Block Truncation Coding (BTC) is a lossy moment preserving quantization method for compressing digital gray level images. Even though this method retains the visual quality of the reconstructed image it shows some artifacts like staircase effect, etc. near the edges. A set of advanced BTC variants reported in literature were analyzed and it was found that though the compression efficiency is increased, the quality of the image has to be improved. An Improved Block Truncation Coding using k-means Quad Clustering (IBTC-KQ) is proposed in this paper to overcome the above mentioned drawbacks. A new approach of BTC to preserve the first order moments of homogeneous pixels in a block is presented. Each block of the input image is segmented into quad-clusters using k-means clustering algorithm so that homogeneous pixels are grouped into the same cluster. The block is then encoded by means of the pixel values in each cluster. Experimental analysis shows an improvement in the visual quality of the reconstructed image with high Peak Signal-to-Noise Ratio (PSNR) values compared to the conventional BTC and other modified BTC methods.
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
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Prentice Hall (2008)
Khalid, S.: Introduction to Data Compression, 3rd edn. (2005)
Baxes, G.A.: Digital Image Processing – Principles and Applications, pp. 179–179. John Wiley & Sons (1994)
Delp, E.J., Mitchell, O.R.: Image Compression Using Block Truncation Coding. IEEE Trans. Commun. 27(9), 1335–1342 (1979)
Lema, M.D., Mitchell, O.R.: Absolute Moment Block Truncation Coding and Its Application to Color Image. IEEE Trans. Commun. 32, 1148–1157 (1984)
Cheng, S.C., Tsai, W.H.: Image Compression by Moment-Preserving Edge Detection. Pattern Recogn. 27, 1439–1449 (1994)
Desai, U.Y., Mizuki, M.M., Masaki, I., Horn, B.K.P.: Edge and Mean Based Compression. MIT Artif. Intell. Lab. AI Memo 1584 (1996)
Amarunnishad, T.M., Govindan, V.K., Abraham, T.M.: Improving BTC Image Compression Using a Fuzzy Complement Edge Operator. Signal Process. Lett. 88, 2989–2997 (2008)
Amarunnishad, T.M., Govindan, V.K., Abraham, T.M.: A Fuzzy Complement Edge Operator. In: IEEE Proceedings of the Fourteenth International Conference on Advanced Computing and Communications, Mangalore, Karnataka, India (2006)
Kumar, A., Singh, P.: Enhanced Block Truncation Coding for Gray Scale Image. Int. J. Comput. Techn. Appl. 2(3), 525–530 (2011)
Kumar, A., Singh, P.: Futuristic Algorithm for Gray Scale Image based on Enhanced Block Truncation Coding. Int. J. Comput. Inform. Syst. 2, 53–60 (2011)
Kanungo, T., Mount, D.M., Netanyahu, N., Piatko, C., Silverman, R., Wu, A.Y.: An efficient k-means clustering algorithm: Analysis and implementation. In: Proceeding IEEE Conference of Computer Vision and Pattern Recognition, pp. 881–892 (2002)
Doaa, M., Fatma, A.: Image Compression Using Block Truncation Coding. Cyber J.: Multidiscipl. J. Sci. Techn. J. Sel. Areas Telecom. (2011)
Eskicioglu, A.M., Fisher, P.S.: Image Quality Measures and Their Performance. IEEE Trans. Commun. 34, 2959–2965 (1995)
Yamsang, N., Udomhunsakul, S.: Image Quality Scale (IQS) for Compressed Images Quality Measurement. In: Proceedings of the International Multiconference of Engineers and Computer Scientists, vol. 1, pp. 789–794 (2009)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image Quality Assessment: from Error Measurement to Structural Similarity. IEEE Trans. Image Process. 13 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mathews, J., Nair, M.S., Jo, L. (2012). Improved BTC Algorithm for Gray Scale Images Using K-Means Quad Clustering. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34478-7_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-34478-7_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34477-0
Online ISBN: 978-3-642-34478-7
eBook Packages: Computer ScienceComputer Science (R0)