Leveraging Fine-Grained Information and Noise Decoupling for Remote Sensing Change Detection

arXiv:2404.11318v1 Announce Type: new
Abstract: Change detection aims to identify remote sense object changes by analyzing data between bitemporal image pairs. Due to the large temporal and spatial span of data collection in change detection image pairs, there are often a significant amount of task-specific and task-agnostic noise. Previous effort has focused excessively on denoising, with this goes a great deal of loss of fine-grained information. In this paper, we revisit the importance of fine-grained features in change detection and …

abstract arxiv change collection cs.cv data data collection detection fine-grained identify image information noise object sense sensing spatial temporal type