Open Access Journal

ISSN : 2394 - 6849 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

ISSN : 2394-6849 (Online)

De-Noising, Enhancement and Developmental Analysis for Fetal Images

Author : Shamya Shetty 1 Dr. Jose Alex Mathew 2

Date of Publication :7th May 2016

Abstract: Medical Image Processing has broadened in recent years. To monitor the behavior of the fetal ultrasound images are considered. These images provide the view of internal organs of the body. But ultrasound images have the drawback of having speckle noise. The quality of the image gets reduced due to the presence of speckle noise. Hence, it is necessary to reduce the speckle noise and to enhance the quality of the image for further images analysis. The detection of any movement as well as the development of the fetus can be analyzed after the preprocessing steps. The system helps the pregnant women to take care of her health stage by stage.

Reference :

  1. [1] Richard N. Czerwinski, Member, IEEE, Douglas L. Jones, Senior Member, IEEE,and William D. O’Brien, Jr., Fellow, ―Detection of Lines and Boundaries in Speckle Images—Application to Medical Ultrasound‖, IEEE Transactions on Medical Imaging, vol. 18, no. 2, february 1999

    [2] D.L.Donoho,‖De-noising by softthresholding,‖ IEEE Transactions on Information Theory, vol. 41, pp. 613–627, 1995

    [3] M.K.Mihc-ak, I.Kozintsev, K.Ramchandran, P.Moulin, ―Low complexity image De-noising based on statistical modeling of wavelet coefficients,‖ IEEE Signal Processing Letters, vol.6 (12) pp.300–303, 1999.

    [4] S.G.Chang, B.Yu, M.Vetterli, ―Spatially adaptive wavelet thresholding with Context modeling for image Denoising,‖ IEEE Transaction on Image Processing, vol.9 (9), pp.1522–1531, 2000.

    [5] A.Pizurica, W.Philips, I.Lamachieu, M.Acheroy, ―A joint inter and intrascale statistical model for Bayesian wavelet based image De-noising,‖ IEEE Transaction on Image Processing, vol.11 (5), pp.545–557, 2002.

    [6] R. Gonzalez, R.E. Woods, Digital Image Processing, Upper Saddle River, NJ, Prentice Hall, 2002


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