2021 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) 2021
DOI: 10.1109/whispers52202.2021.9483963
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A Vector Median Filter For Hyperspectral Images Based On Lexicographic Ordering of Estimated Auto-Correlation Functions

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Cited by 3 publications
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“…Feature extraction methods include: feature extraction method based on binary discrete wavelet transform [10], fast dimensionality reduction method based on dynamic programming [11]. In addition to dimensionality reduction of the data [12], another method for high-dimensional problems is band selection, such as independent component analysis (ICA) for band selection [13]; The bands containing more information are selected by evaluating the average weight coefficient of each band, using an adaptive band weight measurement method based on information entropy [14]. These methods of deleting redundant bands reduce the computational complexity of hyperspectral image classification and ease the high-dimensional problem to a certain extent [15].…”
Section: Introductionmentioning
confidence: 99%
“…Feature extraction methods include: feature extraction method based on binary discrete wavelet transform [10], fast dimensionality reduction method based on dynamic programming [11]. In addition to dimensionality reduction of the data [12], another method for high-dimensional problems is band selection, such as independent component analysis (ICA) for band selection [13]; The bands containing more information are selected by evaluating the average weight coefficient of each band, using an adaptive band weight measurement method based on information entropy [14]. These methods of deleting redundant bands reduce the computational complexity of hyperspectral image classification and ease the high-dimensional problem to a certain extent [15].…”
Section: Introductionmentioning
confidence: 99%