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Lossless Grey-scale Image Compression Using Source Symbols Reduction and Huffman Coding
Saravanan C, Ponalagusamy R
Pages - 246 - 251     |    Revised - 30-10-2009     |    Published - 30-11-2009
Volume - 3   Issue - 5    |    Publication Date - November 2009  Table of Contents
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KEYWORDS
lossless image compression, source symbols reduction, Huffman coding
ABSTRACT
Usage of Images have been increased and used in many applications. Image compression plays vital role in saving storage space and saving time while sending images over network. A new compression technique has been proposed to achieve more compression ratio by reducing number of source symbols. The source symbols are reduced by applying source symbols reduction and further the Huffman Coding is applied to achieve compression. The source symbols reduction technique reduces the number of source symbols by combining together to form a new symbol. Thus the number of Huffman Code to be generated also reduced. The Huffman code symbols reduction achieves better compression ratio. The experiment has been conducted using the proposed technique and the Huffman Coding on standard images. The experiment result has been analyzed and the result shows that the newly proposed compression technique achieves 10% more compression ratio than the regular Huffman Coding.
CITED BY (15)  
1 McGuire, P. C., Bonnici, A., Bruner, K. R., Gross, C., Ormö, J., Smosna, R. A., ... & Wendt, L. (2014). The Cyborg Astrobiologist: matching of prior textures by image compression for geological mapping and novelty detection. International Journal of Astrobiology, 13(03), 191-202.
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3 Saravanan, C., & Bengal, W. Detection of People Faces in a Group Photo.
4 Sarker, M. M. EZW Algorithm and Computation of Its Coefficients for Image Compression by Using “Bottom-Up” Approach.
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6 Saravanan, C., & Surender, M. (2013). Enhancing Efficiency of Huffman Coding using Lempel Ziv Coding for Image Compression. International Journal of Soft Computing and Engineering, ISSN, 2231-2307.
7 Du Shiying. (2012) A new algorithm for lossless image compression. Computer age, (8), 24-25.
8 Chandran, S. (2012). A Novel Technique to Detect Faces in a Group Photo. International Journal of Computer Applications, 54(1).
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10 Kumar, B., Thakur, K., & Sinha, G. R. (2012). A new Hybrid JPEG Symbol Reduction Image Compression Technique. The International Journal of Multimedia & Its Applications (IJMA) Vol, 4, 81-92.
11 Hasan, M., & Md Nur, K. (2012). A novel spatial domain lossless image compression scheme. International Journal of Computer Applications, 39(15), 25-28.
12 Hasan, M., & Nur, K. M. (2012). A Lossless Image Compression Technique using Location Based Approach. International Journal of Scientific & Technology Research, 1(2).
13 Kekre, H. B., Sange, S. R., Sawant, G. S., & Lahoty, A. A. (2011). Image Compression Using Halftoning and Huffman Coding. In Technology Systems and Management (pp. 221-226). Springer Berlin Heidelberg.
14 Al-Hashemi, R., & Kamal, I. W. (2011). A New Lossless Image Compression Technique Based on Bose, Chandhuri and Hocquengham (BCH) Codes. International Journal of Software Engineering and Its Applications, 5(3).
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Dr. Saravanan C
National Institute of Technology - India
trysaran@gmail.com
Professor Ponalagusamy R
National Institute of Technology - India