Nov 12, 2021 · This letter proposes an unsupervised band selection (BS) algorithm named residual driven BS (RDBS) to address the lack of a priori ...

Abstract—This paper proposes an unsupervised band selection. (BS) algorithm, named residual driven BS (RDBS) to address the.

This letter proposes an unsupervised band selection (BS) algorithm named residual driven BS (RDBS) to address the lack of a priori information about ...

Aug 5, 2024 · Dynamic ensemble selection has emerged as a promising approach for hyperspectral image classification. However, selecting relevant features ...

Based on that, a selection criterion is constructed to adaptively select a subset of bands that essentially contain discriminative and informative features ...

The band redundancy for HSI and the spectral similarity between different bands may cause the problem that background and anomalies are difficult to separate in ...

Abstract. Dynamic ensemble selection has emerged as a promising approach for hyperspectral image classification. However, selecting relevant features and ...

Nov 10, 2022 · Band selection (BS) is an effective pre-processing way to reduce the redundancy of hyperspectral data. Specifically, the band prioritization ...

Index Terms—Data-driven projection, hyperspectral ... A is the residual part including anomaly, A ∈ Rb×N . ... Wang et al., “Band subset selection for anomaly ...

Mar 2, 2022 · The band subset selection method finds bands in which the anomaly–background separation is higher than in the original space, which improves per ...