Component adaptive sparse representation for hyperspectral image classification
Author:
Funder
University Grants Commission
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00500-024-09951-1.pdf
Reference44 articles.
1. Barman B, Patra S (2019) A novel technique to detect a suboptimal threshold of neighborhood rough sets for hyperspectral band selection. Soft Comput 23(24):13,709–13,719
2. Bhardwaj K, Patra S, Bruzzone L (2019) Threshold-free attribute profile for classification of hyperspectral images. IEEE Trans Geosci Remote Sens 57(10):7731–7742
3. Bortiew A, Patra S, Bruzzone L (2023) Active learning for hyperspectral image classification using kernel sparse representation classifiers. IEEE Geosci Remote Sens Lett 20:1–5
4. Cavallaro G, Dalla Mura M, Benediktsson JA et al (2016) Remote sensing image classification using attribute filters defined over the tree of shapes. IEEE Trans Geosci Remote Sens 54(7):3899–3911
5. Chen Y, Nasrabadi N, Tran T (2010) Sparsity-based classification of hyperspectral imagery. In: 2010 IEEE International Geoscience and Remote Sensing Symposium, IEEE, pp 2796–2799
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