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Bouida Ahmed
Tahri Mohammed University of Bechar
Electrical & Electronics Engineering

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Hybrid medical image compression method using quincunx wavelet and geometric actif contour Haouam Imane; Beladgham Mohammed; Bouida Ahmed
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (801.012 KB) | DOI: 10.11591/eei.v9i1.1675

Abstract

The purpose of this article is to find an efficient and optimal method of compression by reducing the file size while retaining the information for a good quality processing and to produce credible pathological reports, based on the extraction of the information characteristics contained in medical images. In this article, we proposed a novel medical image compression that combines geometric active contour model and quincunx wavelet transform. In this method it is necessary to localize the region of interest, where we tried to localize all the part that contain the pathological, using the level set for an optimal reduction, then we use the quincunx wavelet coupled with the set partitioning in hierarchical trees (SPIHT) algorithm. After testing several algorithms we noticed that the proposed method gives satisfactory results. The comparison of the experimental results is based on parameters of evaluation.
Co-Authors Beladgham Mohammed Haouam Imane