This study investigates method to reduce the computational complexity of plane-wave ultrasound imaging while maintaining high image quality. The proposed approach constructs B-mode images using sparse data for pixel-based beamforming, followed by up-sampling with interpolation to generate high-resolution B-mode images. Four interpolation techniques—linear, spline, cubic, and Lanczos—were evaluated through ultrasound simulations of point scatterer on sparse data. The performance of each method was assessed by analyzing the full width at half maximum (FWHM) and peak sidelobe level (PSL) of the point spread function. Results demonstrate that sparse data reconstruction achieves an 80.32% reduction in processing time and a 75.05% memory saving for focalized data preserving the same image quality using lanczos interpolation, making it the most effective scheme for reconstructing high-resolution B-mode images.