title: Improved DCT-based nonlocal means filter for MR images denoising.
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.
authors.affiliation: College of Computer Science, Sichuan University, Chengdu 610064, China. dewhjr@hotmail.com
authors.forename: Jinrong
authors.initials: J
authors.lastname: Hu
authors.forename: Yifei
authors.initials: Y
authors.lastname: Pu
authors.forename: Xi
authors.initials: X
authors.lastname: Wu
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhang
authors.forename: Jiliu
authors.initials: J
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D001921:Brain; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007717:Knee; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical