Comput Math Methods Med - Improved DCT-based nonlocal means filter for MR images denoising.

Tópicos

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Resumo

The nonlocal 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 based on the discrete cosine transform (DCT). Instead of computing similarity weights using the gray level information directly, the proposed method calculates similarity weights in the DCT subspace of neighborhood. Due to promising characteristics of DCT, such as low data correlation and high energy compaction, the proposed filter is naturally endowed with more accurate estimation of weights thus enhances denoising effectively. The performance of the proposed filter is evaluated qualitatively and quantitatively together with two other NLM filters, namely, the original NLM filter and the unbiased NLM (UNLM) filter. Experimental results demonstrate that the proposed filter achieves better denoising performance in MRI compared to the others.

Resumo Limpo

nonloc mean nlm filter proven effici featurepreserv denois method can appli remov nois magnet reson mr imag suppress nois effici present novel nlm filter base discret cosin transform dct instead comput similar weight use gray level inform direct propos method calcul similar weight dct subspac neighborhood due promis characterist dct low data correl high energi compact propos filter natur endow accur estim weight thus enhanc denois effect perform propos filter evalu qualit quantit togeth two nlm filter name origin nlm filter unbias nlm unlm filter experiment result demonstr propos filter achiev better denois perform mri compar other

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