We have previously introduced a k-space based 2D post-beamforming filter for restoring image contrast loss due to coarse sampling of the imaging apertures. The 2D regularized imaging operator was obtained and implemented on full frame data in k-space using computationally-efficient 2D fast Fourier transform (FFT). The computational efficiency of the 2D filter can be further improved by implementing the filter in the spatial domain provided the filter has finite region of support (ROS). We have developed a weighting algorithm for limiting the ROS to approximately 0.03% of the full k-space implementation. The algorithm was verified using Field II in imaging a specklegenerating cyst phantom. We simulated two 25 MHz linear arrays with λ /2 and with 2λ element spacing. The simulation results verify that the 2D spatial filter with finite ROS can achieve the same level of restoration in CR while maintaing the same level of spatial resolution achieved by the full k-space filtering approach. We also present the first experimental verification of the performance of our 2D PIO approach on linear array imaging of quality assurance phantom with contrast targets. RF frame data from cystic targets were collected and processed using an appropriately designed 2D PIO. The results show that the CR values were increased by approximately 8 dB without significant reduction in spatial resolution.