A hyperspectral image classification method, system, electronic device and storage medium
By introducing the Grassmann principal angle margin hyperspectral image classification model, combined with 3D-2D spatial-spectral joint feature extraction and dual-stream geodesic attention module, the limitations of Euclidean metric and the problem of unknown category recognition in open scenes of hyperspectral image classification are solved, and high-precision known category classification and unknown category detection are achieved.
CN122368656APending Publication Date: 2026-07-10CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
- Filing Date
- 2026-06-05
- Publication Date
- 2026-07-10
Smart Images
Figure CN122368656A_ABST
Abstract
This invention belongs to the field of computer vision and image processing, specifically providing a hyperspectral image classification method, system, electronic device, and storage medium. The method includes: preprocessing hyperspectral images of the same type of land cover to obtain multiple hyperspectral image patches; constructing a Grassman principal margin hyperspectral image classification model for open scenes; and classifying the hyperspectral images to obtain classification detection results for known or unknown categories. The Grassman principal margin hyperspectral image classification model in this invention introduces the perspective of manifold geometry into the HSI classification scenario under open sets for the first time. Through manifold structure analysis and geodesic distance measurement, it accurately distinguishes between known and unknown categories, providing a novel solution to the HSI classification problem in open scenes.
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