Image Compression based on Fixed Predictor Multiresolution Thresholding of Linear Polynomial Nearlossless Techniques

Authors

  • Ghadah Al-Khafaji Dept. of Computer Science, Baghdad University, College of Science.
  • Shaymaa Fadhil Dept. of Computer Science, Baghdad University, College of Science.

DOI:

https://doi.org/10.29304/jqcm.2017.9.2.311

Keywords:

Image compression, fixed predictor, wavelet transform, linear polynomial and nearlossless techniques.

Abstract

Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information

Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual.

In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless compression scheme of first stage that corresponding to second stage.

The tested results shown are promising  in both two stages, that implicilty enhanced the performance of traditional polynomial model in terms of compression ratio , and preresving image quality.

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Published

2017-11-19

How to Cite

Al-Khafaji, G., & Fadhil, S. (2017). Image Compression based on Fixed Predictor Multiresolution Thresholding of Linear Polynomial Nearlossless Techniques. Journal of Al-Qadisiyah for Computer Science and Mathematics, 9(2), Comp Page 35 – 44. https://doi.org/10.29304/jqcm.2017.9.2.311

Issue

Section

Math Articles