Open Access Open Access  Restricted Access Subscription or Fee Access

High Efficient Image Compression Using Lempel-Ziv-Welch Algorithm

K. Rajeswari, K. Kavitha, G. Boopathi Raja

Abstract


Nowadays, the multimedia applications faces several issues in the storage and transmission of image, video and audio data. This made the field of developing image compression methods necessary and vital. Image compression aims to reduce the redundancy of an image data. This paper introduces the concept of Lempel–Ziv–Welch (LZW) algorithm with Block Truncation method. LZW is a universal lossless algorithm for image compression which has the advantages of low computation load and less memory requirement. This algorithm is widely used in UNIX file and gif image format. This proposed technique is used to increase the Compression Ratio (CR), Peak Signal to Noise Ratio (PSNR), and Mean Square Error (MSE)


Keywords


Block Truncation, Compression Ratio, Image compression, LZW, MSE, PSNR.

Full Text:

PDF

References


M. Mozammel Hoque Chowdhury and Amina Khatun, “Image Compression Using Discrete Wavelet transform,” IJCSI International Journal of Computer Science Issues, Vol.9, Issue 4, No1, July 2012.

S. Bhavani and K.Thanushkodi, “A Survey on Coding Algorithms in Medical Image Compression”, International Journal on Computer Science and Engineering, Vol.02, No. 05, pp. 1429-1434, 2010.

Ghalep, N.H, “Image Compression Using Multiresolution Techniques by Wavelet Transform”, University of AL-Mustansiryah, M.Sc Thesis, 2004.

Lisa, A. S, “The Mathematical Foundation of Image Compression” The University of North Carolina at Wilmington, M.Sc Thesis May 2000.

M.J. Weinberger, G.Seroussi and G.Sapiro, “The LOCO-I lossless image compression algorithm: Principles and standardization into JPEG-LS”, IEEE Trans. on Image Processing, Vol.2, pp.1309-1324, Aug. 2000.

Madhuri A. Joshi, “Digital Image Processing, An Algorithmic Approach”, PHI, New Delhi, pp.175-217, 2006.

Pratishta Gupta, G.N. Purohit and Varsha Bansal “A Survey on Image Compression Techniques,” International Journal of Advanced research in Computer and Communication Engineering, Vol.3, Issue 8, August 2014.

Fränti P. Nevalainen O. and Timo Kaukoranta “Compression of Digital Images by Block Truncation Coding: A Survey” The Computer Journal, 37 (4), 308-332, 1994.

Kumar D. “A Study of Various Image Compression Techniques”, available at http://rimtengg.com/coit 2007/proceedings/pdfs/43.pdf.

J. Ziv and A. Lempel, “A universal algorithm for sequential data compression", IEEE Trans. Inf. Theory, vol. IT-23, no. 3, pp. 337–343, Mar.1977.

Ziv, J, and Lempel, A. “Compression of Individual Sequences via Variable-Rate Coding", IEEE Trans. On Inf. Theory IT-24, 5 (Sept. 1978), pp. 530-536.

Amit Makkar, Gurjit Singh, Rajneesh Narula, “Improving LZW Compression” International Journal of Computer Science And Technology Vol. 3, Issue 1, 411-414, Jan. - March 2012.

Yang and Bourbakis, “An Overview of Lossless Digital Image Compression Techniques,” Circuits & Systems, 2005 48th Midwest Symposium ,vol. 2 IEEE, pp 1099-1102, 7–10 Aug 2005.

G. Prabhakar and B.Ramasubramanian, “An Integrated and Efficient approach for Enhanced Medical Image Compression using SPIHT and LZW Coding,” International Journal of Scientific & Engineering Research Volume 4, Issue 2, February-2013.

Abhayaratne , G. C. K., and Monro, D. M., “Embedded to Lossless Image Coding” University of Bath, United Kingdom Department of Electronic and Electrical Engineering, 2002.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.