title: Compressive sensing for ultrasound RF echoes using a-Stable Distributions.
abstract: This paper introduces a novel framework for compressive sensing of biomedical ultrasonic signals based on modelling data with stable distributions. We propose an approach to ℓ(p) norm minimisation that employs the iteratively reweighted least squares (IRLS) algorithm but in which the parameter p is judiciously chosen by relating it to the characteristic exponent of the underlying alpha-stable distributed data. Our results show that the proposed algorithm, which we prefer to call S ± S-IRLS, outperforms previously proposed ℓ(1) minimisation algorithms, such as basis pursuit or orthogonal matching pursuit, both visually and in terms of PSNR.
authors.affiliation: Department of Electrical & Electronic Engineering, University of Bristol, BS8 1UB, UK. alin.achim@bristol.ac.uk
authors.forename: Alin
authors.initials: A
authors.lastname: Achim
authors.forename: Benjamin
authors.initials: B
authors.lastname: Buxton
authors.forename: George
authors.initials: G
authors.lastname: Tzagkarakis
authors.forename: Panagiotis
authors.initials: P
authors.lastname: Tsakalides
mesh_terms: D000465:Algorithms; D011846:Radio Waves; D014463:Ultrasonography