Vowel onset point (VOP) is an important information extensively employed in speech analysis and synthesis. Detecting the VOPs in a given speech sequence, independent of the text contexts and recording environments, is a challenging area of research. Performance of existing VOP detection methods have not yet been extensively studied in varied environmental conditions. In this paper, we have expl...

Since their introduction in image denoising, the family of non-local methods, whose Non-Local Means (NL-Means) is the most famous member, has proved its ability to challenge other powerful methods such as wavelet based approaches or variational techniques. Though simple to implement and efficient in practice, the classical NL-Means algorithm suffers from several limitations: noise artifacts are...

This paper addresses the problem of accurate voxel-level estimation of tissue proportions in the human brain magnetic resonance imaging (MRI). Due to the finite resolution of acquisition systems, MRI voxels can contain contributions from more than a single tissue type. The voxel-level estimation of this fractional content is known as partial volume coefficient estimation. In the present work, t...

A feature-preserving non-local means (FP-NLM) filter has been developed recently for denoising images containing small and weak particlelike objects. It explores the commonly used non-local means filter to employ two similarity measurements taken in the original greyscale image and a feature image which measures the particle probability in the original image. In this paper, we report a new appr...

Among various kinds of image denoising methods, the Perona–Malik model is a representative Partial Differential Equation based (PDE-based) algorithm which effectively removes the noise as well as having edge enhancement simultaneously through anisotropic diffusion controlled by the diffusion coefficient. However, the unstable behavior of the Perona–Malik model introduces staircasing artifacts i...