Compressive Sensing for Ultrasound RF Echoes Using α-Stable Distributions
نویسندگان
چکیده
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 `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 SαS-IRLS, outperforms previously proposed `1 minimisation algorithms, such as basis pursuit or orthogonal matching pursuit, both visually and in terms of PSNR.
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