Earticle

초록

영어

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.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Wavelet Thresholding De-Noising
  3.1. Thresholding
  3.2. Hard Thresholding
  3.3. Soft Thresholding
 4. Modeling process
  4.1. Data collection
  4.2. Wavelet Selection
  4.3. Hard and Soft Threshold
  4.4. Calculation & Comparison of PSNR and MSE
 5. Experimental Results and Discussion
 6. Conclusion and Future Scope
 Acknowledgements
 References
 Appendix A: Results with Visu Shirnk

키워드

저자

• Saima Anwar Lashari [ Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia ]
• Rosziati Ibrahim [ Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia ]
• Norhalina Senan [ Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605