Recursive Prediction for Lossless Image Compression

Authors

  • Rana Talib Al-Timimi Department of Finance and Banking Science, College of Economics and administration, Mustansiriyah University, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2021.62.10.28

Keywords:

Polynomial Coding, Lossless Image Compression, Fixed Predictor, Image Compression

Abstract

     This paper introduced an algorithm for lossless image compression to compress natural and medical images. It is based on utilizing various casual fixed predictors of one or two dimension to get rid of the correlation or spatial redundancy embedded between image pixel values then a recursive polynomial model of a linear base is used.

The experimental results of the proposed compression method are promising in terms of preserving the details and the quality of the reconstructed images as well improving the compression ratio as compared with the extracted results of a traditional linear predicting coding system.

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Published

2021-10-30

How to Cite

Al-Timimi, R. T. . (2021). Recursive Prediction for Lossless Image Compression. Iraqi Journal of Science, 62(10), 3697–3704. https://doi.org/10.24996/ijs.2021.62.10.28

Issue

Section

Computer Science