Efficient and robust denoising of magnetic resonance brain images based on wavelet based nonlocal means algorithm

-----------------------------------------------------------ABSTRACT---------------------------------------------------------Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). In the proposed method noisy image is first decomposed into subband by wavelet transform and the nonlocal means filter is applied to each subband. This proposed method preserves the wavelet coefficients corresponding to the structures, while effectively suppressing noisy ones. Experimental results are also compared with the other different techniques like median, wiener, wavelet, wavelet based wiener, non-local mean. The quality of the output images is measured by the statistical quantity measures such as peak signal-tonoise ratio (PSNR), signal-to-noise ratio (SNR) and Mean square error (MSE) .The quantitative and the qualitative measures used as the quality metrics demonstrate the ability of the proposed method for noise suppression.