Power-Efficient Image Storage: Leveraging Super Resolution Generative Adversarial Network for Sustainable Compression and Reduced Carbon Footprint

arXiv:2404.04642v1 Announce Type: cross
Abstract: In recent years, large-scale adoption of cloud storage solutions has revolutionized the way we think about digital data storage. However, the exponential increase in data volume, especially images, has raised environmental concerns regarding power and resource consumption, as well as the rising digital carbon footprint emissions. The aim of this research is to propose a methodology for cloud-based image storage by integrating image compression technology with SuperResolution Generative Adversarial Networks (SRGAN). Rather than storing images …

abstract adoption adversarial arxiv carbon carbon footprint cloud cloud storage cloud storage solutions compression concerns consumption cs.ai cs.lg data data storage digital digital data eess.iv environmental generative generative adversarial network however image images network power resolution scale solutions storage super resolution sustainable the way think type