Abstract:
Image denoising and compression has remained a fundamental problem in the
field of image processing aiming at the removal of noise which may corrupt
an image during its acquisition or transmission while sustaining its quality.
Wavelets gave a superior performance in image denoising and compression due
to its properties such as multi resolution.In this thesis an adaptive method
of image denoising in the wavelet sub band domain has been proposed.The
idea behind using this technique the DWT process the horizontal ,vertical
and diagonal details of the image without affect the approximation details,
it improves the performance of the mathematical software(MATLAB) of denoising
function. The experimental evaluation shows that it removes noise
significantly and more effectively than the existed denoise technique it show
that by applying different wavelet family types, different noise level and different
level of decomposition.In the second phase of thesis after image became
free of noise the compression technique jpeg 2000 has been applied to the
image due to the development and demand of multimedia product grows increasingly
fast, contributing to insufficient bandwidth of network and storage
of memory device. Therefore, the theory of data Compression is useful because
it helps reduce the consumption of expensive resources such as hard
disk space or transmission bandwidth.In this thesis, the fundamental theory
of image compression in chapter 2 has been briefly introduced,two typical
standards JPEG and JPEG 2000 will be described and implemented to the
denoise image in chapter 4. The last given image is compressed denoise image
without degraded its quality.
