Numerous studies have been conducted for hyperspectral image (HSI) classification by assuming that the label information of training data is fully available and correct. However, such an assumption may not always be true in practical applications, which could impact feature extraction methods and eventually compromise the performance of hyperspectral image classification. To address this issue in hyperspectral image classification, we propose a Regularized Fuzzy Discriminant Analysis (RFDA) based feature extraction method to effectively utilize...
