MR Images Denoising Using DCT-Based Unbiased Nonlocal Means Filter

The non-local means (NLM) filter has been proven to be an efficient feature-preserved denoising method and can be applied to remove noise in the magnetic resonance (MR) images. To suppress noise more efficiently, we present a novel NLM filter by using a low-pass filtered and low dimensional version of neighborhood for calculating the similarity weights. The discrete cosine transform (DCT) is used as a smoothing kernel, allowing both improvements in similarity estimation and computational speed-up. Experimental results show that the proposed filter achieves better denoising performance in MR Images compared to others filters, such as recently proposed NLM filter and unbiased NLM (UNLM) filter.