Sidelobes-Free Wavelet-Based Chirp Compression for Ultrasound Imaging

Chirp-coded excitation improves signal-to-noise ratio in ultrasound imaging, but conventional matched filtering introduces high sidelobes that degrade image quality. Alternatives such as mismatched filtering reduce resolution, while Wiener filtering depends on accurate SNR estimation and may amplify noise. In this work, we adapt the Fourier–Wavelet Regularized Deconvolution (ForWaRD) algorithm for chirp compression, exploiting shrinkage in both Fourier and wavelet domains. Simulations and experiments demonstrate that the proposed wavelet-based filter outperforms conventional methods by combining high axial resolution with strong sidelobe suppression and effective noise reduction.