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Noise Removal in Spatial Domain for MRI Images Through Non-Linear Filters with Varying Window Size


Smita Agrawal , NIELIT GORAKHPUR; Kamlesh Kumar Samota, NIELIT GORAKHPUR; Umang Varshney, NIELIT GORAKHPUR


HMF (Hybrid Median Filter), Gaussian Filter, Adaptive Wiener Filter, Standard Median Filter, Weighted Median Filter, Average Filter, SNR (Signal to Noise Ratio), PSNR (Peak SNR), MSE (Mean Square Error)


Noise Removal is a major issue in Biomedical Image Processing. Ultrasound spectroscopy and Magnetic Resonance Image (MRI) require highly efficient output images for analysis. Various techniques exist in literature for filtering noisy images. The type of filtering is highly dependent upon the noise density, window size of the filter and the type of noise. In this paper, various filtering techniques for noise removal from MRI images are discussed. Two types of filtering approaches are employed in noise removal: Linear filtering and Non-Linear filtering. Each type is described in detail along-with their advantages as well as disadvantages in a particular domain. The filters are implemented in MATLAB.

Other Details

Paper ID: IJSRDV5I70155
Published in: Volume : 5, Issue : 7
Publication Date: 01/10/2017
Page(s): 238-243

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