Remote sensing imagery is crucial for global monitoring but often limited by sensor spatial resolution and the high cost of acquiring ultra-high-resolution data. The Sentinel-2 (S2) mission provides multispectral imagery across 13 bands at 10m, 20m, and 60m resolutions. However, these resolutions may not capture fine details required for tasks like land cover mapping, agricultural monitoring, or disaster assessment. Super-Resolution (SR) technology addresses this by reconstructing high-resolution images from low-resolution inputs, significantly enhancing spatial detail in S2 imagery for more precise data support.