红外技术2025，Vol.47Issue(5)：601-610,10.
基于局部对比度和多向梯度的高光谱异常检测
Hyperspectral Anomaly Detection Based on Local Contrast and Multidirectional Gradients
摘要
Abstract
To fully utilize the spatial and spectral information of hyperspectral images and suppress image noise,a hyperspectral anomaly detection method based on local contrast and multidirectional gradient analysis is proposed.First,to leverage local spectral information,a local contrast strategy is introduced,generating a spectral detection score map based on the brightness difference between the target and the background.Then,to reduce computational complexity,a spectral fusion-based dimensionality reduction technique is proposed to process hyperspectral images.In addition,a local multidirectional gradient feature method is proposed to reduce image noise,retain local detail features,and generate a multidirectional gradient detection score map.Finally,the anomaly result map is obtained by fusing the spectral and gradient-based score graphs.Experimental results on four classical datasets demonstrate that the proposed method can successfully display abnormal targets in the result graph,achieving higher detection accuracy and lower false alarm rates compared to seven existing methods.关键词
高光谱图像/异常检测/局部对比度/光谱融合降维/多向梯度特征Key words
hyperspectral image/anomaly detection/local contrast/spectral fusion dimensionality reduction/multi-directional gradient features分类
计算机与自动化引用本文复制引用
武丽,徐星臣,王一安,任佳红,张嘉嘉,赵东,王新蕾..基于局部对比度和多向梯度的高光谱异常检测[J].红外技术,2025,47(5):601-610,10.基金项目
国家自然科学基金(2105258) （2105258）
江苏省自然科学基金(BK20210064) （BK20210064）
无锡市创新创业资金"太湖之光"科技攻关计划(基础研究)项目(K20221046) （基础研究）
无锡学院人才启动基金(2021r007). （2021r007）
