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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Unsupervised Band Selection by Integrating the Overall Accuracy and Redundancy
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Unsupervised Band Selection by Integrating the Overall Accuracy and Redundancy

机译：集成整体精度和冗余度的无监督频段选择

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摘要

Band selection is of great significance to alleviate the curse of dimensionality for hyperspectral (HSI) image application. In this letter, we propose a novel unsupervised band selection method for HSI classification. This method integrates both the overall accuracy and redundancy into the band selection process by formulating an optimization model. In the optimization problem, an adaptive balance parameter is designed to trade off the overall accuracy and redundancy. Additionally, we adopt an unsupervised overall accuracy prediction method to obtain the overall accuracy; thus, no ground truth or training samples is required. Experimental results on the ROSIS and RetigaEx data sets show that our method outperforms four representative methods in terms of classification accuracy and redundancy.
机译：频带选择对于减轻高光谱（HSI）图像应用的维数诅咒具有重要意义。在这封信中，我们提出了一种用于HSI分类的新型无监督频带选择方法。该方法通过制定优化模型，将整体精度和冗余度整合到了频段选择过程中。在优化问题中，设计了一个自适应平衡参数来权衡总体精度和冗余度。此外，我们采用无监督的整体准确性预测方法来获得整体准确性；因此，不需要地面事实或训练样本。在ROSIS和RetigaEx数据集上的实验结果表明，在分类准确性和冗余性方面，我们的方法优于四种代表性方法。

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