Considerations on unsupervised spectral data unmixing and complexity pursuit

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Hyperspectral sensors carry the distinctive advantage of recording hundreds of contiguous spectral images for the same scene providing an extraordinary amount of information that leads to precise differentiation of materials present in the scene even when such materials contribute only to few pixels [1]. With the advent of more and more powerful sensing platforms, coupled with reduction in manufacturing costs and diversification of technologies, hyperspectral imaging has become a powerful approach in remote sensing with applications spanning all traditional fields (such as agriculture, mining, military, resource management, etc.) as well as new ones (manufacturing quality control, pollution detection, health and life sciences, food safety etc.

Original languageEnglish
Title of host publication2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
Pages987-990
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2010
Event2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 - Honolulu, HI, United States
Duration: 25 Jul 201030 Jul 2010

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Other

Other2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
CountryUnited States
CityHonolulu, HI
Period25/07/1030/07/10

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Robila, S. (2010). Considerations on unsupervised spectral data unmixing and complexity pursuit. In 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 (pp. 987-990). [5649574] (International Geoscience and Remote Sensing Symposium (IGARSS)). https://doi.org/10.1109/IGARSS.2010.5649574