文章基本信息

标题：Wavelet Threshold De- Noising for Mammogram Images
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作者：Saima Anwar Lashari ; Rosziati Ibrahim ; Norhalina Senan 等
期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2015
卷号：9
期号：6
页码：215-226
DOI：10.14257/ijseia.2015.9.6.20
出版社：SERSC
摘要：Digital mammograms are coupled with noise which makes de-noising a challenging problem. In the literature, few wavelets like daubechies db3 and haar have been used for de-noising medical images. However, wavelet filters such as sym8, daubechies db4 and coif1 at certain level of soft and hard threshold have not been taken into account for mammogram images. Therefore, in this study five wavelet filters namely: haar, sym8, daubechies db3, db4 and coif1 at certain level of soft and hard threshold have been considered. Later, peak signal to noise ratio and mean squared error values are calculated. From the obtained results, it can be concluded that db3 (46.44656 db for hard threshold and 43.80779 db for soft threshold) is more appropriate filter for de-noising mammogram images while compared with other wavelets filters
关键词：Wavelet de-noising; hard thresholding; soft thresholding; peak signal to ; noise ratio