In this paper, we propose the DSR-QBD framework, which integrates Deep Burst Super-Resolution (DBSR) with U-Net-based 2x2 OCL Quad-Bayer Demosaic. Traditional single-frame methods often struggle with the inherent disparity issues present in 2×2 On-Chip Lens (OCL) Quad-Bayer sensors. Our proposed framework addresses these challenges by treating a single 2×2 OCL image as multiple phase-separated frames, enabling the application of advanced multi-frame super-resolution techniques. Unlike conventional single-frame approaches, our method addresses the disparity issue in 2×2 OCL Quad-Bayer sensors by treating a single 2×2 OCL image as multiple phase-separated frames and applying multi-frame techniques. This strategy enables the effective utilization of phase images to enhance reconstruction quality. Furthermore, the integration of U-QBD within DSR-QBD mitigates the limitations of DBSR, particularly in correcting false pattern artifacts that may arise during reconstruction, thereby yielding more stable and natural results.