Wavelet Sparse Representation based Beam-forming for Ultrasound Imaging: Theory and Simulation

In this paper, a wavelet sparse representation based beamforming is proposed to improve the resolution and contrast of plane wave emission ultrasound imaging. First, the received signals are described as the convolution of the target scatterers with the point spread function of the system. And then, the wavelet sparse representation model is deduced according to the fact that the target scatterers can be sparse represented in wavelet domain. The proposed algorithm was tested with simulated ultrasound data in plane wave emission. And the results demonstrated that the resolution was clearly improved and contrast ratio gains of 9.8 dB, 4.3 dB and 3.7 dB were obtained compared to delay-and-sum beamformer, minimum variance beamformer and phase coherence factor, respectively.