Name
Abstract | ||
|---|---|---|
Change detection by unmixing has been shown to provide enhanced change detection performance for hyperspectral images with respect to more traditional approaches, especially when the temporal images contain sub-pixel level changes. In a recent paper, change detection by spectral unmixing was investigated in detail and the advantages that can be gained by using such an approach were systematically presented through various experimental studies. However, the utilized unmixing-based change detection approach relied solely on spectral information and disregarded the spatial distribution in the scene, which inevitably limits the performance that can be achieved. In this paper, superpixels are used to integrate the spatial information in the image into the unmixing process, which in turn enhances the change detection performance with respect to spectral unmixing based change detection. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IGARSS.2016.7729871 | 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) |
Keywords | Field | DocType |
Change detection, hyperspectral imaging, multitemporal, superpixels, unmixing | Spatial analysis,Computer vision,Algorithm design,Full spectral imaging,Change detection,Pattern recognition,Computer science,Remote sensing,Image segmentation,Hyperspectral imaging,Artificial intelligence,Aerospace electronics | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Erturk | 1 | 102 | 15.81 |
| S. Erturk | 2 | 548 | 51.19 |
| Antonio Plaza | 3 | 3475 | 262.63 |