We use five dimensionality reduction methods-PCA, KPCA, ICA, AE, and DAE-to compress 301-dimensional hyperspectral pixels.  We found that PCA, KPCA, and ICA post greater signal reconstruction capability; however, when compression rates are more than 90% these methods show lower classification scores. 
PCA
We use five dimensionality reduction methods-PCA, KPCA, ICA, AE, and DAE-to compress 301-dimensional hyperspectral pixels.  We found that PCA, KPCA, and ICA post greater signal reconstruction capability; however, when compression rates are more than 90% these methods show lower classification scores. 
KPCA
The effects of spectral dimensionality reduction on hyperspectral pixel classification: A case study.This paper presents a systematic study of the effects of hyperspectral pixel dimensionality reduction on the pixel classification task.  We use five dimensionality reduction methods-PCA, KPCA, ICA, AE, and DAE-to compress 301-dimensional hyperspectral pixels.  Compressed pixels are subsequently used to perform pixel classifications.  Pixel classification accuracies together with compression method, compression rates, and reconstruction errors provide a new lens to study the suitability of a compression method for the task of pixel classification.  We found that PCA, KPCA, and ICA post greater signal reconstruction capability; however, when compression rates are more than 90% these methods show lower classification scores.  AE and DAE methods post better classification accuracy at 95% compression rate, however their performance drops as compression rate approaches 97%.  Our results suggest that both the compression method and the compression rate are important considerations when designing a hyperspectral pixel classification pipeline.
ICA
We use five dimensionality reduction methods-PCA, KPCA, ICA, AE, and DAE-to compress 301-dimensional hyperspectral pixels.  AE and DAE methods post better classification accuracy at 95% compression rate, however their performance drops as compression rate approaches 97%. 
AE
We use five dimensionality reduction methods-PCA, KPCA, ICA, AE, and DAE-to compress 301-dimensional hyperspectral pixels.  AE and DAE methods post better classification accuracy at 95% compression rate, however their performance drops as compression rate approaches 97%. 
DAE