Mammographic image enhancement using wavelet transform and homomorphic filter

Majidi, F; Latif, A M; Malakouti, J; Kasayi, H

doi:10.18869/acadpub.ijpr.15.3.305

Mammographic image enhancement using wavelet transform and homomorphic filter

Authors

F Majidi

A M Latif

J Malakouti

H Kasayi

https://doi.org/10.18869/acadpub.ijpr.15.3.305

Abstract

Mammography is the most effective method for the early diagnosis of breast cancer diseases. As mammographic images contain low signal to noise ratio and low contrast, it becomes too difficult for radiologists to analyze mammogram. To deal with the above stated problems, it is very important to enhance the mammographic images using image processing methods. This paper introduces a new image enhancement approach for mammographic images which uses the modified mathematical morphology, wavelet transform and homomorphic filter to suppress the noise of images. For performance evaluation of the proposed method, contrast improvement index (CII) and edge preservation index (EPI) are adopted. Experimental results on mammographic images from Pejvak Digital Imaging Center (PDIC) show that the proposed algorithm improves the two indexes, thereby achieving the goal of enhancing mammographic images.

Keywords

mammographic images

image processing

Wavelet transform

homomorphic filter

1. V K Gunturu and A Sharma IEEE (2010) 323.
2. S Amutha, D R Ramesh Babu, M Ravi Shankar, and N Harish Kumar, IEEE (2011) 548.
3. N Harish Kumar, S Amutha and D R Ramesh Babu, IJCTA (2012) 192.
4. T Stojic, I Reljin and B Reljin, IEEE (2005) 609.
5. Walid Dabour, CSSE (2008) 948.
6. Y Meyer, “Wavelets Algorithms and Applications”, SIAM, Philadelphia, PA (1993).
7. S Mallat, “A Wavelet Tour of Signal Processing”, Academic Press, New York (1998).
8. C K Chui, “Wavelets: A Mathematical Tool for Signal Processing,” SIAM, Philadelphia, PA (1997).
9. A Laine, S Song, Procidings of Mathematical Methods Med. Imaging, D.C. Wilson, J.N. Wilson Eds., SPIE 1768 (1992) 306.
10. A Laine, J Fan, and S Schuler, Proceedings of the Second International Workshop on Digital Mammography, Eds A.G. Gale, et al., (1994) 91.
11. A Laine, S Schuler, J Fan, and W Huda, IEEE Trans. Med. Imaging 13, 4 (1994) 725.
12. W Qian, P Clarke, M Kallergi, H D Li, R Velthuizen, R A Clark, and M L Silbiger, Biomedical Image Processing and Biomedical Visualization, Proc. SPIE, 1905, Eds R.S. Acharya, D.B. Goldgof, (1993) 509.
13. Y Yoshida, K Doi, R M Nishikawa, T Ema, and W Zhang, Medical Imaging, Proc. SPIE 2167 (1994) 868.
14. R N Strichland and H I Hahn, IEEE Trans. Med. Imaging 15, 2 (1996) 218.
15. H D Cheng and H J Xu, “A Novel Fuzzy Logic Approach to Mammogram Contrast Enhancement”, Elsevier Science Inc (2002) 167.
16. J Hyun Yoon and Y Man Ro, Ieice Trans. INF. & SYST., E85-D, 1 January (2012).