Optical remote sensing images of cities exhibit strong spectral variability, and characterising it remains a key challenge. Imaging spectroscopy is useful for this purpose, yet traditional endmember extraction algorithms are poorly suited for this type of imagery. Important issues include the non-spatiality, randomness and poor computational efficiency of existing methods, as well as the need for predefining the number of endmembers. We propose a novel algorithm, called Iterative Spectral Distancing addressing each of these issues. We show that ISD outperforms three established methods on a synthetic image, indicating its potential.
|Titel||2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS|
|ISBN van geprinte versie||978-166540369-6|
|Status||Published - 2021|
|Evenement||IGARSS 2021 - Brussels, Belgium|
Duur: 12 jul 2021 → 16 jul 2021
|Periode||12/07/21 → 16/07/21|