Applications of Wavelet Transform in Registration, Segmentation, Denoising, and Compression of Medical Images - Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE-2012) - page 111

Applications of Wavelet Transform
in Registration, Segmentation, Denoising,
and Compression of Medical Images
Neelu Dubey, Meghna Jain and Mukta Bhatele
Abstract Wavelet transforms and other multiscale analysis functions have been
used for compact signal and image representations in denoising, compression, and
feature detection processing problems. The wavelet transform itself offers great
design flexibility. Basis selection, spatial-frequency tiling, and various wavelet
threshold strategies can be optimized for best adaptation to a processing appli-
cation, data characteristics, and feature of interest. Fast implementation of wavelet
transforms using a filter-bank framework enables real-time processing capability.
Instead of trying to replace standard image processing techniques, wavelet trans-
forms offer an efficient representation of the signal, finely tuned to its intrinsic
properties. By combining such representations with simple processing techniques
in the transform domain, multiscale analysis can accomplish remarkable perfor-
mance and efficiency for many image processing problems.
Keywords Wavelet transform using Matlab Image edge detection Segmen-
tation Registration De-noising Lossless image compression Digital imaging
and communications in medicine (DICOM) Security issue in transmission
Transmission of medical images Measuring lossless compression effectiveness
parameters Compression algorithm
N. Dubey
CTA, Gyan Ganga College of Technology, Jabalpur, India
M. Jain ( & )
Digital Communication, Gyan Ganga College of Technology, Jabalpur, India
e-mail: [e-mail]
M. Bhatele
Department of Computer Science, Gyan Ganga College of Technology, Jabalpur, India
e-mail: [e-mail]