Multi-Stage Convolutional Broad Learning with Block Diagonal Constraint for Hyperspectral Image Classification

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 17; p. 3412
• Main Authors: Kong, Yi, Wang, Xuesong, Cheng, Yuhu, Chen, C. L. Philip
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2021
• Subjects: Approximation; Artificial neural networks; block diagonal; broad learning system; Classification; Constraints; convolutional neural network; Deep learning; Feature extraction; Feature selection; hyperspectral image; Hyperspectral imaging; Image classification; Information processing; Learning; Mapping; Methods; Multilayers; Neural networks; Principal components analysis; Remote sensing

By combining the broad learning and a convolutional neural network (CNN), a block-diagonal constrained multi-stage convolutional broad learning (MSCBL-BD) method is proposed for hyperspectral image (HSI) classification. Firstly, as the linear sparse feature extracted by the conventional broad learni...