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LiDAR-Guided Cross-Attention Fusion for Hyperspectral Band Selection . . . Our method integrates band selection with the fusion model and has demonstrated superior classification performance compared to full-band fusion models Specifically, it has shown a notable increase in the overall accuracy, average accuracy, and Kappa coefficients across multiple data sets
Band Selection for Hyperspectral Images: A Survey - IRJET formation is removed using band selection method This is he first stage of hyperspectral image processing The selection of appropriate spectral bands from hundreds of narrow bands can be done based on different statistical parameters, distance metric algo
Fusion of Various Band Selection Methods for Hyperspectral Imagery - MDPI Two versions of BSF, called progressive BSF and simultaneous BSF, are developed for this purpose Of particular interest is that BSF can prioritize bands without band de-correlation, which has been a major issue in many BS methods using band prioritization as a criterion to select bands
Enhanced hyperspectral image analysis via 2D-3D CNN fusion . . . - Springer To tackle these issues, this paper presents a progressive framework for hyperspectral image analysis and classification This framework combines 2D-3D Convolutional Neural Networks (CNN) with a Hybrid Moth-Flame Optimization (MFO) technique for optimal band selection
Residual-Driven Band Selection for Hyperspectral Anomaly Detection Abstract—This letter proposes an unsupervised band selec-tion (BS) algorithm named residual driven BS (RDBS) to address the lack of a priori information about anomalies, obtain a band subset with high representation capability of anomalies, and finally improve the anomaly detection (AD)
HSLiNets: Evaluating Band Ordering Strategies in Hyperspectral and . . . In this work, we systematically investigate the influence of band order on HSI-LiDAR fusion performance Through extensive experiments, we demonstrate that band order significantly impacts classification accuracy, revealing a previously overlooked factor in fusion-based models