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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 3 Issue 5, 2012.
Abstract: Nowadays, Digital image acquisition and processing techniques plays a very important role in current day medical diagnosis. During the acquisition process, there could be distortions in the images, which will negatively affect the diagnosis images. In this paper a new technique based on the hybridization of wavelet filter and center weighted median filters is proposed for denoising multiple noise (Gaussian and Impulse) images. The model is experimented on standard Digital Imaging and Communications in Medicine (DICOM) images and the performances are evaluated in terms of peak signal to noise ratio (PSNR), Mean Absolute Error (MAE), Universal Image Quality Index (UQI) and Evaluation Time (ET). Results prove that utilization of center weighted median filters in combination with wavelet thresholding filters on DICOM images deteriorates the performance. The proposed filter gives suitable results on the basis of PSNR, MSE, UQI and ET. In addition, the proposed filter gives nearly uniform and consistent results on all the test images.
J UMAMAHESWARI and Dr.G.RADHAMANI, “Hybrid Denoising Method for Removal of Mixed Noise in Medical Images” International Journal of Advanced Computer Science and Applications(IJACSA), 3(5), 2012. http://dx.doi.org/10.14569/IJACSA.2012.030507
@article{UMAMAHESWARI2012,
title = {Hybrid Denoising Method for Removal of Mixed Noise in Medical Images},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2012.030507},
url = {http://dx.doi.org/10.14569/IJACSA.2012.030507},
year = {2012},
publisher = {The Science and Information Organization},
volume = {3},
number = {5},
author = {J UMAMAHESWARI and Dr.G.RADHAMANI}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.