Name
Abstract | ||
|---|---|---|
Superpixel segmentation has been demonstrated to be a powerful tool in hyperspectral image (HSI) classification. Each superpixel region can be regarded as a homogeneous region, which is composed of a series of spatial neighboring pixels. However, a superpixel region may contain the pixels from different classes. To further explore the optimal representations of superpixels, a new framework based o... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JSTARS.2018.2872969 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Hyperspectral imaging,Image segmentation,Feature extraction,Training,Transforms,Image edge detection | Hyperspectral image classification,k-nearest neighbors algorithm,Computer vision,Filter (signal processing),Feature extraction,Hyperspectral imaging,Image segmentation,Interference (wave propagation),Pixel,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
11 | 11 | 1939-1404 |
Citations | PageRank | References |
2 | 0.35 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bing Tu | 1 | 18 | 11.69 |
| Jin-Ping Wang | 2 | 12 | 3.25 |
| Xudong Kang | 3 | 451 | 22.68 |
| Guoyun Zhang | 4 | 18 | 7.38 |
| Xianfeng Ou | 5 | 26 | 6.56 |
| Longyuan Guo | 6 | 10 | 4.59 |