IDF-CR: Iterative Diffusion Process for Divide-and-Conquer Cloud Removal in Remote-sensing Images

arXiv:2403.11870v1 Announce Type: new
Abstract: Deep learning technologies have demonstrated their effectiveness in removing cloud cover from optical remote-sensing images. Convolutional Neural Networks (CNNs) exert dominance in the cloud removal tasks. However, constrained by the inherent limitations of convolutional operations, CNNs can address only a modest fraction of cloud occlusion. In recent years, diffusion models have achieved state-of-the-art (SOTA) proficiency in image generation and reconstruction due to their formidable generative capabilities. Inspired by the rapid development of diffusion models, we …

abstract arxiv cloud cnns convolutional neural networks cs.cv deep learning diffusion eess.iv however images iterative limitations networks neural networks operations optical process remote-sensing sensing tasks technologies type