Implementation and Comparison of Various Filters for the Removal of Fractional Brownian Motion Noise in Brain MRI Images
Abstract: Recently in all medical imaging systems, noise plays a dominant role in suppressing the useful information needed for diagnosis and hence, doctors are finding a great difficulty in analyzing the progression of the disease. This paper deals with removal of one such noise, namely fractional Brownian motion noise by using various filters such as mean filter, alpha trimmed mean filter, contra harmonic mean filter, wiener filter and homomorphic filter. The performance of all these filters are compared using evaluation metrics such as PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), NAE (Normalized Absolute Error) and the time elapsed to filter the noisy image. Among all the filters, homomorphic filter proves to be better in terms of PSNR, MSE, NAE and time elapsed.
Index Terms -- Alpha trimmed mean filter, contra harmonic mean filter, exponential, homomorphic filter, logarithmic transform, mean filter, wiener filter.
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International Journal for Trends in Technology & Engineering © 2015 IJTET JOURNAL