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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Velez-Reyes, M. Rosario, S. |
| Copyright Year | 2004 |
| Description | Author affiliation: Lab. for Appl. Remote Sensing & Image Process., Puerto Rico Univ. (Velez-Reyes, M.; Rosario, S.) |
| Abstract | This paper presents an algorithm for abundance estimation in hyperspectral imagery. The fully constrained abundance estimation problem where the positivity and the sum to less than or equal to one (or sum equal to one) constraints are enforced is solved by reformulating the problem as a least distance (LSD) least squares (LS) problem. The advantage of reformulating the problem as a least distance problem is that the resulting LSD problem can be solved using a duality theory using a nonnegative LS problem (NNLS). The NNLS problem can then be solved using Hanson and Lawson algorithm or one of several multiplicative iterative algorithms presented in the literature. The paper presents the derivation of the algorithm |
| Starting Page | 3276 |
| Ending Page | 3278 |
| File Size | 596964 |
| Page Count | 3 |
| File Format | |
| ISBN | 0780387422 |
| DOI | 10.1109/IGARSS.2004.1370401 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-09-20 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Hyperspectral sensors Hyperspectral imaging Iterative algorithms Spatial resolution Reflectivity Analytical models Noise measurement Gaussian noise Laboratories Remote sensing |
| Content Type | Text |
| Resource Type | Article |
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