Hyperspectral images unmixing with rare signals

Abstract

Pixels in hyperspectral images are a mixing of source signals. Hyperspectral unmixing is an important issue in image processing. In this paper we consider a linear mixing model. We address the unmixing issue when some "rare" source signals are only present in few mixed pixels. We propose a new method based on Non-negative Matrix Factorization (NMF) with known endmembers' number. This method first estimates the abundant source signals. Then it detects pixels which contain the rare signals. Finally it processes those pixels to estimate the rare signals.