Improved DCT-Based Nonlocal Means Filter for MR Images Denoising

Author:

Hu Jinrong12,Pu Yifei1,Wu Xi3,Zhang Yi1,Zhou Jiliu1

Affiliation:

1. College of Computer Science, Sichuan University, Chengdu 610064, China

2. College of Computer Science, Sichuan University, Chengdu 610065, China

3. College of Electronic and Information Engineering, Sichuan University, Chengdu 610064, China

Abstract

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.

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine

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