Research progress on anomaly target detection algorithms for hyperspectral imagery
Year: 2025
Type: article
Abstract: Hyperspectral image (HSI) data plays an important role in remote sensing images, and researchers have done a great deal of work to understand and recognize HSI. Among them, hyperspectral image-anomaly target detection (HSI-ATD) has numerous applications in both national defense, military, and civilian fields. In particular, because anomaly target detection does not require any prior information, it has become one of the key technologies and research hotspots in HSI processing and information extraction. Through systematic sorting and analysis, this paper summarizes the existing anomaly target detection algorithms in detail, and evaluates the key issues involved in HSI-ATD, future technological development directions (such as deep learning, multimodal, and real-time processing, etc), as well as the problems existing in the algorithms. Additionally, some innovative viewpoints and predictions on future research trends are proposed.
Source: Geocarto International
Authors: Baozhi Cheng, Yan Gao
Institution: Changzhou Institute of Technology
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,390
OpenAlex ID: W4416867368