Document Type
Conference Proceeding
Publication Date
12-1-2010
Journal / Book Title
2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
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.
DOI
10.1109/IGARSS.2010.5649574
Montclair State University Digital Commons Citation
Robila, Stefan, "Considerations on Unsupervised Spectral Data Unmixing and Complexity Pursuit" (2010). Department of Computer Science Faculty Scholarship and Creative Works. 188.
https://digitalcommons.montclair.edu/compusci-facpubs/188
Published Citation
Robila, S. A. (2010). Considerations on unsupervised spectral data unmixing and complexity pursuit. In 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 (pp. 987-990). Article 5649574 (International Geoscience and Remote Sensing Symposium (IGARSS)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2010.5649574
