Steganography is the practice which involves the covert embedding of a confidential payload within a designated cover medium to prevent unintended recipients from detecting the presence of hidden information. Steganographic systems are designed to address four key properties: Imperceptibility, security, payload capacity, and robustness. While traditional algorithms have achieved high levels of security and imperceptibility, they often suffer from low payload capacity and susceptibility to image noise and degradation. This paper introduces a robust deep steganographic system that employs pretrained super-resolution models for payload reconstruction. The goal is to diminish the recognizable signature of the payload image within the cover image while ensuring a high payload capacity during the reconstruction process.