# MOSAIC

Remote sensing super-resolution previously injected low-resolution observations as dense spatial conditions into a diffusion Transformer, so small foreground objects were easily diluted by dominant backgrounds. MOSAIC organizes degraded observations into compact object-level and layout-level structural slots, fuses them across resolutions, and retrieves recurring structural priors from a shared prototype memory, then injects them into a frozen DiT4SR backbone through lightweight residual modulation. On UCMerced, AID and RSSCN7, PSNR is best at both scales, exceeding DiT4SR by 2.03 dB on UCMerced, 4.54 dB on AID and 1.49 dB on RSSCN7, with the lowest LPIPS on RSSCN7 and AID.

Remote sensing super-resolution previously injected low-resolution observations as dense spatial conditions into a diffusion Transformer, so small foreground objects were easily diluted by dominant backgrounds. MOSAIC organizes degraded observations into compact object-level and layout-level structural slots, fuses them across resolutions, and retrieves recurring structural priors from a shared prototype memory, then injects them into a frozen DiT4SR backbone through lightweight residual modulation. On UCMerced, AID and RSSCN7, PSNR is best at both scales, exceeding DiT4SR by 2.03 dB on UCMerced, 4.54 dB on AID and 1.49 dB on RSSCN7, with the lowest LPIPS on RSSCN7 and AID.