Paper Info
Title
Mammogram Enhancement Using Lifting Dyadic Wavelet Transform and Normalized Tsallis Entropy.
Abstract
In this paper, we present a new technique for mammogram enhancement using fast dyadic wavelet transform (FDyWT) based on lifted spline dyadic wavelets and normalized Tsallis entropy. First, a mammogram image is decomposed into a multiscale hierarchy of low-subband and high-subband images using FDyWT. Then noise is suppressed using normalized Tsallis entropy of the local variance of the modulus of oriented high-subband images. After that, the wavelet coefficients of high-subbands are modified using a non-linear operator and finally the low-subband image at the first scale is modified with power law transformation to suppress background. Though FDyWT is shift-invariant and has better potential for detecting singularities like edges, its performance depends on the choice of dyadic wavelets. On the other hand, the number of vanishing moments is an important characteristic of dyadic wavelets for singularity analysis because it provides an upper bound measurement for singularity characterization. Using lifting dyadic schemes, we construct lifted spline dyadic wavelets of different degrees with increased number of vanishing moments. We also examine the effect of these wavelets on mammogram enhancement. The method is tested on mammogram images, taken from MIAS (Mammographic Image Analysis Society) database, having various background tissue types and containing different abnormalities. The comparison with the state-of-the-art contrast enhancement methods reveals that the proposed method performs better and the difference is statistically significant.
Year
DOI
Venue
2014
10.1007/s11390-014-1489-7
J. Comput. Sci. Technol.
Keywords
Field
DocType
mammogram enhancement, lifting dyadic wavelet transform, Tsallis entropy
Spline (mathematics),Normalization (statistics),Pattern recognition,Computer science,Upper and lower bounds,Singularity,Tsallis entropy,Artificial intelligence,Gravitational singularity,Wavelet,Wavelet transform
Journal
Volume
Issue
ISSN
29
6
1860-4749
Citations 
PageRank 
References 
1
0.42
11
Authors
2
Name
Order
Citations
PageRank
muhammad110.42
Muhammad Hussain242234.28