Abstract:
The medical images carry very sensitive data in order to detect the abnormalities in the
organ of a body. These images contain huge information and the images size is too large
to store the images, that’s why it requires huge space causing an extra cost and the images
are affected by different noises during transmission. The bandwidth management can
grounds the extra cost, so compression can be the solution to overcome the drawbacks.
The aims of the project is to compress the medical image in a popular existing method of
Wavelet 2D analysis. The project is divided into 2 parts as the noisy image analysis and
de-noised image analysis. The noises are added in the image and de-noised images are
considered to analysis the actual susceptibility to the actual images. The noisy images and
de-noised images are analyzed in the Wavelet 2D and different variations are observed by
their statistical analysis. The compression ratio of different compression threshold methods are also compared in the result section and performance of different filter has also
been observed
