Title :
Spatial enhancement of hyperion hyperspectral data through ALI panchromatic image
Author :
Capobianco, Luca ; Garzelli, Andrea ; Nencini, Filippo ; Alparone, Luciano ; Baronti, Stefano
Author_Institution :
Univ. of Siena, Siena
Abstract :
This paper presents two novel image fusion methods, suitable for sharpening of hyperspectral (HS) images by means of a panchromatic (Pan) observation: the HS bands expanded to the finer scale of the Pan image are sharpened by adding the spatial details which are calculated by the PAN image. Since a direct, unconditioned injection of Pan details gives unsatisfactory results, a new injection model is proposed, which provides the optimum injection simulating fusion at degraded scale by minimizing the mean square error. Fusion tests are carried out both on spatially degraded data to objectively compare the proposed scheme to some fusion methods and on full resolution image data.
Keywords :
image enhancement; image fusion; terrain mapping; ALI panchromatic image; hyperion hyperspectral data; image fusion methods; injection simulating fusion; panchromatic observation; spatial enhancement; Data mining; Degradation; Hyperspectral imaging; Hyperspectral sensors; Image resolution; Mean square error methods; Multispectral imaging; Spatial resolution; Strontium; Testing;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
DOI :
10.1109/IGARSS.2007.4424023