杨京辉:Joint Collaborative Representation With Shape Adaptive Region and Locally Adaptive Dictionary for Hyperspectral Image Classification
2021-03-04 发布:[信息工程学院] 点击:23次
A novel hyperspectral image (HSI) classification method based on joint collaborative representation with shape adaptive region and locally adaptive dictionary (SALJCR) is proposed in this letter. First, the shape adaptive (SA) region is selected for each pixel to exploit the neighboring spatial information adaptively. The average filtering (according to SA regions) is performed for the whole image. Then, based on the filtered image, a locally adaptive dictionary is constructed for each test pixel to reduce the negative impact of irrelevant pixels on representation. Finally, a joint collaborative representation method is applied to decompose the pixels and assign the class label. Experimental results demonstrate that the proposed SALJCR method outperforms some state-of-the-art classifiers.
上述成果发表在期刊《IEEE GEOSCIENCE AND REMOTE SENSING LETTERS》上:Yang,JH(Yang,Jinghui)[1];Qian,JX(Qian,Jinxi)[2]. Joint Collaborative Representation With Shape Adaptive Region and Locally Adaptive Dictionary for Hyperspectral Image Classification. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,17(4):671-675.
全文链接:https://ieeexplore.ieee.org/document/8793155
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校址:北京市海淀区学院路29号
邮编:100083
技术支持:信息网络与数据中心
@版权所有:中国地质大学(北京)
文保网安备案:1101080023