Lossy Images Compression Based on Multiresolution

Authors

  • rana talib gdeeb AL-Mustansiriyah University

DOI:

https://doi.org/10.23851/mjs.v29i2.242

Keywords:

Lossy image compression, Multiresolution, and Linear prediction

Abstract

A hybrid lossy compression system was presented in this paper. It was based on combining the multiresolution coding together with a polynomial approximation of linear base to decompose grey images followed by an efficient coding. The test results showed promising performance where the compression ratio improved about three times or more compared with the results of the traditional linear predicting coding system.

Downloads

Download data is not yet available.

Author Biography

  • rana talib gdeeb, AL-Mustansiriyah University
    computer science Lecturer

References

M. Hemalatha, S. Nithya, “A Thorough Survey on Lossy Image Compression Techniques”, International Journal of Applied Engineering Research, 2016, vol. 11, no. 5, pp. 3326-3329.

G. Sadashivappa, and Ananda Babu, “Performance Analysis of Image Coding Using Wavelets”, International Journal of Computer Science and Network Security, 2008,vol.8, no.10, pp.144-151.

D. Grigorios , N. Zervas, N. Sklavos, and E. Costas, “Design Techniques and Implementation of Low Power High-Throughput Discrete Wavelet Transform Tilters for JPEG 2000 Standard”, International Journal of Signal Processing, 2008, vol. 4, no. 1, pp. 36-43.

L. E. George, and B. Sultan, “Image Compression Based on Wavelet, Polynomial and Quadtree”, Journal of Applied Computer Science & Mathematics, 2011, vol. 11, no. 5, pp. 15-20.

Al-K. Ghadah, and Al-M. Haider,” Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model”. International Journal of Computer applications, 2013, vol. 76, no. 3, pp. 38-42.

Al-K. Ghadah, Al-K. Hazeem,”Medical Image Compression using Wavelet Quadrants of Polynomial Prediction Coding & Bit Plane Slicing”, 2014, vol. 4, no. 6, pp. 32-36.

Al-K. Ghadah, and L. E. George, “Fast Lossless Compression of Medical Images based on Polynomial”. International Journal of Computer Applications, 2013, vol. 70, no. 15, pp.28-32.

Al-K. Ghadah,“Hybird Image Compression based on Polynomial and Block TruncationCoding”.Electrical Communication Computer, Power and Control Engineering(ICECCPCE) ,IEEE, 2013, pp. 179-184.

Al-T. Rasha, Al-K. Ghadah, “Image Compression Using Hierarchical Linear Polynomial Coding”. International Journal of Computer Science and Mobile Computing, IJCSMC, January 2015, vol. 4, no. 1, pp.112 – 119.

L. E. George, and B.N. Dhannon , “Image Compression Using Polynomial and Quadtree Coding Techniques” , International Journal of Scientific & Engineering Research, 2013,vol. 4, no.11, pp.2229-5518.

H. Al-Mahmood, “Selective Bit Plane Coding and Polynomial Model for Image Compression”, International Journal of Advanced Research in Computer Science and Software Engineering 2014, vol. 4, no.4, pp. 797-801.

] Al-T. Rana, “Lossy Image Compression based on Differential Coding and Linear Polynomial”. Journal of College of Education, 2016, vol.5, pp. 433-442.

Al-K. Ghadah, ”Image Compression based on Quadtree and Polynomial”. International Journal of Computer Applications, 2013, vol. 76, no.3, pp. 31-37.

M. Hemalatha, S. Nithya, “A Thorough Survey on Lossy Image Compression Techniques”, International Journal of Applied Engineering Research, 2016, vol. 11, no. 5, pp. 3326-3329.

Downloads

Key Dates

Published

17-11-2018

Issue

Section

Original Article

How to Cite

[1]
rana talib gdeeb, “Lossy Images Compression Based on Multiresolution”, Al-Mustansiriyah Journal of Science, vol. 29, no. 2, pp. 126–134, Nov. 2018, doi: 10.23851/mjs.v29i2.242.

Similar Articles

1-10 of 85

You may also start an advanced similarity search for this article.