A Non-Reference Diffusion-Based Restoration Framework for Landsat 7 ETM+ SLC-off Imagery in Antarctica
Researchers have developed DiffGF, a novel framework designed to restore corrupted Landsat 7 satellite imagery from Antarctica. This method utilizes a diffusion-based approach in latent and pixel spaces, eliminating the need for external reference data, which is often unavailable or unreliable for the rapidly changing Antarctic landscape. A new dataset, SLCANT, was created to train and evaluate DiffGF, demonstrating its effectiveness in high-fidelity image restoration and its utility in downstream applications like crevasse segmentation. AI
IMPACT Enables better utilization of historical satellite data for environmental monitoring and research in challenging regions.