Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images

Yang, Zhijing; Cao, Faxian; Cheng, Yongqiang; Ling, Wing-Kuen; Hu, Ruo

Abstract

Despite the successful applications of probabilistic collaborative representation classification (PCRC) in pattern classification, it still suffers from two challenges when being applied on hyperspectral images (HSIs) classification: 1) ineffective feature extraction in HSIs under noisy situation; and 2) lack of prior information for HSIs classification. To tackle the first problem existed in PCRC, we impose the sparse representation to PCRC, i.e., to replace the 2-norm with 1-norm for effective feature extraction under noisy condition. In order to utilize the prior information in HSIs, we first introduce the Euclidean distance (ED) between the training samples and the testing samples for the PCRC to improve the performance of PCRC. Then, we bring the coordinate information (CI) of the HSIs into the proposed model, which finally leads to the proposed locality regularized robust PCRC (LRR-PCRC). Experimental results show the proposed LRR-PCRC outperformed PCRC and other state-of-the-art pattern recognition and machine learning algorithms.

Citation

Yang, Z., Cao, F., Cheng, Y., Ling, W., & Hu, R. (in press). Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images. IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society, 1-16. https://doi.org/10.1109/tgrs.2020.2988900

• Journal Article Type: Article
• Acceptance Date: Apr 14, 2020
• Online Publication Date: May 8, 2020
• Deposit Date: Jul 9, 2020
• Publicly Available Date: Jul 10, 2020
• Journal: IEEE Transactions on Geoscience and Remote Sensing
• Print ISSN: 0196-2892
• Electronic ISSN: 1558-0644
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 1-16
• DOI: https://doi.org/10.1109/tgrs.2020.2988900
• Keywords: Coordinate information (CI); Euclidean distance (ED); Hyperspectral image (HSIs); Probabilistic collaborative representation classification (PCRC); Sparse representation
• Public URL: https://hull-repository.worktribe.com/output/3537848
• Publisher URL: https://ieeexplore.ieee.org/document/9089850