In ultrasound (US) imaging, beamforming is usually separated from the deconvolution or some other post-processing techniques. The former processes raw data to build radio-frequency (RF) images while the latter restore high-resolution images, denoted as tissue reflectivity function (TRF), from RF images. This work is the very first trial to perform deconvolution directly with raw data, bridging the gap between beamforming and deconvolution, and thus reducing the estimation errors from two separate steps. The proposed approach retrieves both high quality RF and TRF images and exhibits better RF image quality than a classical beamforming approach.