The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Hyperspectral unmixing is an important issue to analyze hyperspectral data. Based on the present mixing models, this paper proposes a new nonlinear unmixing framework for hyperspectral imagery. The proposed framework transforms the hyperspectral unmixing problem to a constrained nonlinear least squares problem by introducing the abundance nonnegative constraint, abundance sum-to-one constraint and...
In recent years, independent component analysis (ICA) has been applied to unmix the hyperspectral data since it can perform without the prior knowledge of ground objects. The traditional ICA algorithm regards the extracted independent components as unmixing results, which is not reasonable for hyperspectral imagery, because different endmembers are not actually independent from each other. In order...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.