Name
Title | ||
|---|---|---|
Enhanced Spatially Constrained Remotely Sensed Imagery Classification Using a Fuzzy Local Double Neighborhood Information C-Means Clustering Algorithm. |
Abstract | ||
|---|---|---|
This paper presents a fuzzy local double neighborhood information c-means (FLDNICM) clustering algorithm for remotely sensed imagery classification, which incorporates flexible and accurate local spatial and spectral information. First, a tradeoff weighted fuzzy factor is established based on a pixel spatial attraction model that considers spatial distance and class membership differences between ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/JSTARS.2018.2846603 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Remote sensing,Clustering algorithms,Robustness,Image edge detection,Linear programming,Clustering methods,Noise measurement | Computer vision,Pattern recognition,Noise measurement,Segmentation,Fuzzy logic,Outlier,Robustness (computer science),Artificial intelligence,Pixel,Prior probability,Cluster analysis,Mathematics | Journal |
Volume | Issue | ISSN |
11 | 8 | 1939-1404 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hua Zhang | 1 | 28 | 3.13 |
| Lorenzo Bruzzone | 2 | 4952 | 387.72 |
| Wenzhong Shi | 3 | 778 | 86.23 |
| ming hao | 4 | 41 | 4.34 |
| Yunjia Wang | 5 | 71 | 15.63 |