Recursive Least Squares adaptive filters for ultrasonic signal deconvolution

Biomedical ultrasound (US) image quality is limited due to the blurring of tissue reflectivity introduced by the transducer point spread function (PSF). Deconvolution techniques can be used to eliminate this effect and to obtain the pure tissue response. In this paper we propose a new enhancement method based on recursive least squares (RLS) adaptive filtering. The method handles the spatial variability of the PSF by means of blind homomorphic characterization of the transducer. The results show that the RLS adaptation increases contrast and resolution by eliminating the spectral shaping of the backscattered echo and thus enhancing the diagnostic capability of US images.