BOOSTING HYPERSPECTRAL IMAGE UNMIXING USING DENOISING: FOUR SCENARIOS

Publication Type:

Conference Paper

Authors:

Behnood Rasti; Bikram Koirala; Paul Scheunders; Pedram Ghamisi; Richard Gloaguen

Source:

IEEE International Geoscience and Remote Sensing Symposium IGARSS (2021)

Abstract:

We present an analysis of the influence of noise on the unmixing of hyperspectral data. We propose four scenarios to 1) investigate the effect of noise reduction as a preprocessing step on the performance of hyperspectral unmixing and 2) study the relation between noise and different endmembers selection strategies. Experiments are conducted on a simu-1ated and a real datasets with a wide range of signal to noise ratios (from 10 to 50 dB).

Research area: 
Remote sensing