Super-resolution reconstruction of off-axis digital holography based on Real-ESRGAN

Off-axis digital holography plays a crucial role in high-precision three-dimensional imaging. However, high-resolution phase images are often affected by the limited pixel size of the sensor. To address this issue, this study proposes, for the first time, to the best of our knowledge, the application of Real-ESRGAN for the super-resolution reconstruction of off-axis digital holography images. By directly applying super-resolution processing to the hologram, the limitations of the sensor's pixel size are overcome, followed by phase reconstruction to obtain high-resolution phase images. The Real-ESRGAN model enhances the texture information of the hologram through a deep network with multiple residual-in-residual dense blocks (RRDBs), restoring a clearer hologram. A U-Net architecture with spectral normalization, offering stronger discriminative capability, is used to provide detailed per-pixel feedback for the generator. The experimental results demonstrate that this method can be applied to multi-scale holograms, outperforming comparison networks in both visual quality and quantitative metrics, thus providing an innovative solution for the super-resolution reconstruction of off-axis digital holography.