On recent results in demosaicing of Samsung 108MP CMOS sensor using deep learning

There is a recent trend change in using non-Bayer Color Filter Array (CFA) patterns, allowing superior image quality in low-light conditions. However, these new CFA patterns have weak point on full image reconstruction showing severe visual artifacts and low details reconstruction after demosaicing. In this work, we address aforementioned problems by using deep learning approach for new CFA type - Nonacell or Nonapixel, introduced by Samsung 108MP HMX CMOS image sensor. Experimental results show that proposed method not only allows suppression of visual artifacts and perfect details and edge restoration, but also shows superior objective image quality, exceeding 40dB in CPSNR for popular Kodak dataset. Finally, our method is computationally efficient due to network structure and feasible for on-device deployment after optimization.