원문정보
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
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