This code contain two algorithms namely: General Synthesis Prior (GSP) and General Analysis Prior(GAP) for reducing impulse noise from hyperspectral images.
These algorithms utilizes both spatial and spectral correlation.
GSP algorithm uses Daubechies wavelet for spatial dimension and Fourier transform for vertical dimension.
GAP algorithm is based on total variation minimization.
SPARCO toolbox (freely available from : http://www.cs.ubc.ca/labs/scl/sparco/) is required to run the code.
Hemant Kumar Aggarwal (2020). HyperSpectralDenoising.zip (https://www.mathworks.com/matlabcentral/fileexchange/46988-hyperspectraldenoising-zip), MATLAB Central File Exchange. Retrieved .