IMAGE COMPRESSION USING WAVELETS

Image compression enables images for easier data storage and data transmission. One
ofnewest technique used in compressing image is wavelet transform. Wavelet widely
used in application such as medical imaging, internet imaging, scanning and printing,
mobile and digital cameras. Wavelets are new filter that can keep the information in
both time domain and frequency domain. The special about wavelet filter is that the
window can be varied by changing the frequency. The objective of the project is to
create a simulation model to investigate image compression using wavelets. The
investigation will makes comparative study by applying different types of wavelet
techniques on different types of images. The MATLAB software is used in doing
simulation. As necessary background to do the project, basic concept of image
processing, wavelet theory, image compression, and information theory are learned
and discussed. The simulation will use several types of wavelets families including
Haar, Daubachies, Symlet, Coiflet and Biorthogonal Spline wavelets. The papers will
analyze and examine the effect of difference wavelet families, filter order, filter
length, decomposition level and image content and quantizer type in compressing
image. After doing numerous comparisons of wavelet effects on all test images, the
results of the simulation shows that Daubachies wavelets family is having the most
outstanding performance compared to other wavelet families. Hence, Daubachies is
the bestfilter to usein doing wavelet image compression.