2017
Pre-processing and classification of hyperspectral imagery via selective inpainting
ICASSP 2017accepted
We propose a semi-supervised algorithm for processing and classification of hyperspectral imagery. For initialization, we keep 20% of the data intact, and use Principal Component Analysis to discard voxels from noisier bands and pixels. Then, we use either an Accelerated Proximal Gradient algorithm…