Optical Image-to-Image Translation Using Denoising Diffusion Models: Heterogeneous Change Detection as a Use Case

arXiv:2404.11243v1 Announce Type: new
Abstract: We introduce an innovative deep learning-based method that uses a denoising diffusion-based model to translate low-resolution images to high-resolution ones from different optical sensors while preserving the contents and avoiding undesired artifacts. The proposed method is trained and tested on a large and diverse data set of paired Sentinel-II and Planet Dove images. We show that it can solve serious image generation issues observed when the popular classifier-free guided Denoising Diffusion Implicit Model (DDIM) framework …

abstract arxiv case change contents cs.ai cs.cv deep learning denoising detection diffusion diffusion models image images image-to-image image-to-image translation low ones optical resolution sensors translate translation type