Open AccessWAVELET TRANSFORMATION FOR ENHANCING MAMMOGRAPHIC IMAGES
Author(s) -
Ankush Rai,
Jagadeesh Kannan R
Publication year - 2017
Publication title -
asian journal of pharmaceutical and clinical research
Language(s) - English
Resource type - Journals
eISSN - 2455-3891
pISSN - 0974-2441
DOI - 10.22159/ajpcr.2017.v10s1.19739
Subject(s) - wavelet , transformation (genetics) , artificial intelligence , noise reduction , computer science , computer vision , noise (video) , pattern recognition (psychology) , image denoising , task (project management) , image (mathematics) , engineering , biology , biochemistry , systems engineering , gene
Mammographic images are often prone to noises and consequently make the task of radiologist to come up with the precise diagnosis. Though there are several denoising techniques for the same is available but while denoising they often suffers from the problem of eliminating the micron level details in the noise influenced images. It’s a trade-off which prohibits efficient micro-classification of mammary tissues. This, in this study we present a solution for the same by utilizing multi level wavelet transformation to enable preservation of micron level details in the images.