Seeing Through the Clouds: Cloud Gap Imputation with Prithvi Foundation
Model
Seeing Through the Clouds: Cloud Gap Imputation with Prithvi Foundation
Model
Filling cloudy pixels in multispectral satellite imagery is essential for accurate data analysis and downstream applications, especially for tasks which require time series data. To address this issue, we compare the performance of a foundational Vision Transformer (ViT) model with a baseline Conditional Generative Adversarial Network (CGAN) model for missing …