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ABSTRACT
Recently, the information processing approaches are increased. These methods can be used for several pur-
poses: compressing, restoring, and information encoding. The raw data are less presented and are gradually
replaced by others formats in terms of space or speed of access. This paper is interested in compression,
precisely, the image compression using the Haar wavelets. The latter allows the application of compression
at several levels. The subject is to analyze the compression levels to fnd the optimal level. This study is
conducted on medical images.
Application of Haar Wavelets
on Medical Images
R. El Ayachi, Faculty of Science and Technology, Université Sultan Moulay Slimane, Beni
Mellal, Morocco
M. Gouskir, Faculty of Science and Technology, Université Sultan Moulay Slimane, Beni
Mellal, Morocco
M. Baslam, Faculty of Science and Technology, Université Sultan Moulay Slimane, Beni
Mellal, Morocco
Keywords: Compression Level, Haar Wavelets, Image Compressing, Medical Image, Segmentation
1. INTRODUCTION
In recent years, the information is multiplied exponentially. This makes their manipulations
difficult in terms of raw storage and transmission. The solution is to represent the information,
the image that is precisely the goal of this work, in another form in order to overcome these
problems. This change of representation can be performed using the compressing.
The area of image compression is extensively studied and still attracts many researchers
(Tim Bruylants & all, 2015, S. Rupa & all, 2014, Rakotomalala M. A. & all, 2010). This moti-
vation appears in the research and development of algorithms to find other forms of imagerep-
resentation. Furthermore, image compression plays a crucial role in medical imaging, allowing
efficient manipulation, storage, and transmission of binary, grey-scale, or color images.There
are two types of compressing: lossless and lossy. The first type is used for the images that must
remain identical to their originals. The second type is used for images whose quality is limited
to perceptions. Haar wavelets are an example of lossy compressing algorithm.
DOI: 10.4018/JECO.2015040104