On the application of spectral unmixing for noise reduction

Spectral unmixing aims at decomposing each image element of a hyperspectral scene in signals typically related to pure materials. This paper gives an added value to the results of this process by proposing Unmixing-based Denoising (UBD), a supervised methodology to recover bands characterized by a low Signal-to-Noise Ratio in a hyperspectral scene. In the first step of UBD, an unmixing procedure is carried out using a set of reference spectra which are noise-free, as they are averaged over areas for which ground truth is available. Results are inferred into the pixelwise reconstruction of a given band, expressed as a linear combination of the values of the reference spectra in that band, ignoring the residual vector which is mainly characterized by undesired atmospheric influences and sensor-induced noise. The reconstructed images exhibit both high visual quality and reduced spectral distortions.