CFP last date
20 March 2024
Reseach Article

Image Compression with Modified Skipline Encoding and Curve Fitting

by Saumya Sadanandan, V. K. Govindan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 5
Year of Publication: 2013
Authors: Saumya Sadanandan, V. K. Govindan
10.5120/12882-9786

Saumya Sadanandan, V. K. Govindan . Image Compression with Modified Skipline Encoding and Curve Fitting. International Journal of Computer Applications. 74, 5 ( July 2013), 24-30. DOI=10.5120/12882-9786

@article{ 10.5120/12882-9786,
author = { Saumya Sadanandan, V. K. Govindan },
title = { Image Compression with Modified Skipline Encoding and Curve Fitting },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 5 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 24-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number5/12882-9786/ },
doi = { 10.5120/12882-9786 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:41:26.197358+05:30
%A Saumya Sadanandan
%A V. K. Govindan
%T Image Compression with Modified Skipline Encoding and Curve Fitting
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 5
%P 24-30
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

High quality digitized images have always been subject to high correlation: high image quality equals large file size. Image Compression is an important issue in Internet, mobile communication, digital library, digital photography, multimedia, teleconferencing and other applications. Application areas of Image Compression would focus on the problem of optimizing storage space and transmission bandwidth. Here a lossy method for image compression based on skip line encoding and curve fitting is proposed. Proposed approach involves two major processing steps: a lossless modified skip line encoding process to eliminate redundant scan lines in the image, and a lossy curve fitting based encoding for further redundancy elimination. The degree of compression is controlled based on the amount of loss that is affordable for applications making use of Peak Signal to Noise Ratio (PSNR) measure in the decision. The results obtained with the combined, modified skip line encoding and curve fitting approach, are analyzed in terms of compression ratio and PSNR. The approach provides improvements in compression ratio for all the tested images. The results obtained were found to be better than a state-of-the-art method in the literature.

References
  1. E. J. Delp, M. Saenz and Salma, article BLOCK TRUNCATION CODING (BTC), 2010.
  2. O. R Mitchell and E. J. Delp, "Multilevel graphics representation using block truncation coding", proceedings of the IEEE, vol. 68, no. 7, pp. 868-873,July 1980.
  3. J. Polec and J. Pavlovicova,; , "A new version of region based BTC," EUROCON'2001, Trends in communications, International Conference on. , vol. 1, no. , pp. 88-90 vol. 1, 4-7 July 2001.
  4. C. K. Yang, and W. H. Tsai, Improving block truncation coding by line and edge information and adaptive bit plane selection for gray-scale image compression, Pattern recognition letters,volume. 16,number1,pages=67-75,1995.
  5. T. M. Amarunnishad, V. K. Govindan and Abraham T. Mathew, Improved BTC image compression using a fuzzy complement edge operator, signal Processing, vol- 88, issue 12, (2008)2989-2997, Elsevier 2008.
  6. T. M. Amarunnishad, V. K. Govindan and Abraham T. Mathew, Use of Fuzzy Edge Image in Block Truncation Coding for Image compression, International Journal of signal Processing, Vol 4, N0 3, pp 215-221, 2008.
  7. T. M. ¬¬ Amarunnishad, V. K. Govindan and Abraham T. Mathew, Block Truncation Coding with Huffman coding, Journal of medical imaging and health informatics, Vol. 1, No. 2, pp170-176, 2011.
  8. A. Aggoun and A. El-Mabrouk; , "Image compression algorithm using local edge detection," Wireless Image/Video Communications, 1996. , First International Workshop on , vol. , no. , pp. 68-73, 4-5 Sep 1996.
  9. U. Y. Desai, M. M. Mizuki and I. Masakiand Horn; B. K. P. , Edge and mean based image compression,1996.
  10. R. Redondo and G. Cristobal; "Lossless chain coder for gray edge images," Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on , vol. 2, no. , pp. II- 201-4 vol. 3, 14-17 Sept. 2003
  11. D. E. Tamir , K. Phillip and Abdul-Karim, , "Efficient chain-code encoding for segmentation-based image compression," Data Compression Conference, 1996. DCC '96. Proceedings , vol. , no. , pp. 455, Mar/Apr 1996.
  12. Moinuddin A. A, E. Khan, and F. Ghani. An effficient technique for storage of two-tone images. Consumer Electronics, IEEE Transactions on, 43(4):1312-1319, 1997.
  13. H. Sung and W. Y. Kuo. A skip-line with threshold algorithm for binary image compression. In Image and Signal Processing (CISP), 2010 3rd International Congress on, volume 2, pages 515-523. IEEE, 2010.
  14. M. B. Akhtar, A. M. Qureshi and Qamar-ul-Islam, "Optimized run length coding for jpeg image compression used in space research program of IST," Computer Networks and Information Technology (ICCNIT), 2011 International Conference on , vol. , no. , pp. 81-85, 11-13 July 2011.
  15. Ameer, Salah, and Otman Basir. "Image compression using plane fitting with inter block prediction. " Image and Vision Computing 27. 4 (2009): 385-390.
  16. Chen, Y. S. , H. T. Yen, and W. H. Hsu. "Color image coding by using the technique of surface fitting. " Pattern Recognition, 1992. Vol. III. Conference C: Image, Speech and Signal Analysis, Proceedings. , 11th IAPR International Conference on. IEEE, 1992
  17. Ichida, K. , F. Yoshimoto, and T. Kiyono. "Curve fitting by a piecewise cubic polynomial. " Computing 16. 4 (1976): 329-338.
  18. Zamani, Mehdi. "A simple piecewise cubic spline method for approximation of highly nonlinear data. " Advances in Molecular Imaging 4 (2012).
Index Terms

Computer Science
Information Sciences

Keywords

binary images image compression RLE encoding skip-line encoding curve fitting