Quaternion non-local means (QNLM) denoising algorithm makes full use of high degree self-similarities inside images to suppress the noise, so similarity metric plays a key role in its performance. In this study, two improvements have been made for QNLM: 1) For low level quaternion quasi-Chebyshev distance is proposed measure image patches and it has used replace Euclidean QNLM algorithm. Since ...

This article proposes a fast and open-source implementation of the well-known Non-Local Means (NLM) denoising algorithm, in its original pixelwise formulation. The fast implementation is based on the computation of patch distances using sums of lines that are invariant under a patch shift. The optimal parameters of NLM (in the average peak signal to noise ratio PSNR sense) are computed from an ...

Purpose Magnetic resonance spectroscopic imaging (MRSI) is an imaging modality used for studying tissues in-vivo in order to assess and quantify metabolites for diagnostic purposes. However, long scanning times, low spatial resolution, poor signal-to-noise ratio (SNR) and the subsequent noise-sensitive non-linear model fitting are major roadblocks in accurately quantifying the metabolite concen...

The generation process of medical image will inevitably introduce certain noises. These noises will degrade the image quality and affect the final clinical diagnosis. Therefore, denoising plays an important role in the pre-processing of medical image before the formal diagnosis and treatment. In this paper, the classical NLM algorithm is improved to denoise medical images by involving a novel n...

A wide number of magnetic resonance imaging (MRI) analysis techniques rely on brain tissue segmentation. Automated and reliable tissue classification is a challenging task as the intensity of the data typically does not allow a clear delimitation of the different tissue types because of partial volume effects, image noise and intensity non-uniformities caused by magnetic field inhomogeneities. ...