Abstract
Halftoning is the printing technology in which each pixel in halftone image is represented by single bit. Hence halftoning gives 87.5% compression ratio. Modified Huffman encoding technique is used on halftone image for further compression of image data. This algorithm achieves a high compression ratio that ensures optimum utilization of network resources and storage. In our earlier work a small operator of size 3x3 is used, which effectively takes only one tap operation. Floyd-Steinberg operator which takes 5 tap operations has been used. Thus factors, like computational complexity, memory space and image quality, have been considered. The proposed algorithm has been implemented on MATLAB platform and has been tested on various images of size 256x256. The image quality measurement has been done using Mean Square Error and Structural Similarity Index parameters. The proposed technique can be used for storage of images in this hybrid compressed form, and low bit rate data transmission for video conferencing.
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.
References
Sange, S.: A Survey on: Black and White and Color Half toning Techniques. SVKM’s NMIMS University, MPSTME, Journal of science, Engineering & Technology Management 1(2), 7–17 (2009)
Floyd, R.W., Steinberg, L.: An adaptive algorithm for spatial grayscale. Proc. SID 17/2, 75–77 (1976)
Wong, P.: Inverse half toning and Kernel estimation for error diffusion. IEEE Trans. Image Processing 4, 486–498 (1995)
Hein, S., Zakhor, A.: Halftone to continuous–tone conversion of Error-diffusion coded images. IEEE Trans. Images Processing 4, 208–216 (1995)
Kite, T.D., Evans, B.L., Bovik, A.C.: Modeling and Quality Assessment of Half toning by Error Diffusion. IEEE Transaction on Image Processing 9(5) (May 2000)
Sange, S.R.: Image data compression using new Halftoning operators and Run Length Encoding. Springer Explorer and Springer CS Digital Library, pp. 224–230
Kekre, H.B., Sange, S.: Restoration of Color Halftone image by using Fast Inverse Half toning Algorithm. In: International Conference on Advances in Recent Technologies in Communication and Computing. IEEE, Los Alamitos (2009), ISBN: 978-0-7695-3845-7/09
Pujar, J.H., Kadlaskar, L.M.: A New Lossless Method of Image Compression and Decompression Using Huffman Coding Techniques. Journal of Theoretical and Applied Information Technology
Saravanan, C., Ponalagusamy, R.: Lossless Grey-scale Image Compression using Source Symbols Reduction and Huffman Coding. International Journal of Image Processing (IJIP)Â 3(5)
Aggarwal, M., Narayan, A.: Efficient Huffman Decoding. In: 2000 International Conference on Image Processing, Proceedings,
Tehranipour, M.H.: Nourani: Mixed RL-Huffman encoding for power reduction and data compression in scan test. In: 2010 Third International Symposium on Intelligent Information Technology and Security Informatics (IITSI), April 2-4 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kekre, H.B., Sange, S.R., Sawant, G.S., Lahoty, A.A. (2011). Image Compression Using Halftoning and Huffman Coding. In: Shah, K., Lakshmi Gorty, V.R., Phirke, A. (eds) Technology Systems and Management. Communications in Computer and Information Science, vol 145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20209-4_31
Download citation
DOI: https://doi.org/10.1007/978-3-642-20209-4_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20208-7
Online ISBN: 978-3-642-20209-4
eBook Packages: Computer ScienceComputer Science (R0)