Improved Fuzzy Based Non-Local Mean Filter to Denoise Rician Noise
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Abstract
Nowadays MRI has become an important tool to diagnose medical conditions but there is a growing need for a denoise image produced. Rician noise is one of the major challenges in MRI. So the nonlocal means (NLM) filter has gained popularity to denoise medical images as it gives excellent results. In the present work, an Improved Fuzzy-based Non-Local Mean Filter is proposed for denoise Rician noise. In the proposed method the first step is to find the non-local similar pixel in the image using fuzzy function. Then these similar pixels are used to generate noise-free pixels. The above approach is tested with real data and the results are compared with existing Fuzzy techniques by using root mean square error, structural similarity index measure, and peak signal-noise ratio (PSNR) methods. This technique gives better result than the existing Fuzzy Non-Local Mean technique with both high and low-density Rician noise in the image
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