Name
Title | ||
|---|---|---|
High Spatial Resolution Remote Sensing Image Segmentation Using Temporal Independent Pulse-Coupled Neural Network |
Abstract | ||
|---|---|---|
Temporal Independent Pulse-Coupled Neuron Network (TI-PCNN) has been developed and shows its usefulness on digital image segmentation. However, Due to its heavy computational cost and over-segmentation of objects within the range of low intensity, the original TI-PCNN method is ineffective at segmenting High Spatial Resolution remotely sensed Images (HSRI). By taking into account of spatial and spectral characteristics of HSRI, an improved method based on the TI-PCNN was developed and used to segment HSRI. Experiment was carried out on a subset of an aerial image. Result showed that the improved method largely overcomes the drawbacks of the original method and provided a promising approach for HSRI segmentation. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/IGARSS.2007.4423200 | IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET |
Keywords | Field | DocType |
Temporal-Independent Pulse-Coupled Neuron Network, segmentation, high spatial resolution remote sensing image | Computer vision,Computer science,Segmentation,Remote sensing,Digital image,Image segmentation,Aerial image,Remote sensing image segmentation,Artificial intelligence,Artificial neural network,Image resolution | Conference |
Volume | Issue | ISSN |
null | null | 2153-6996 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liwei Li | 1 | 0 | 0.34 |
| Jianwen Ma | 2 | 28 | 12.35 |
| Chen Xue | 3 | 15 | 8.77 |
| Wen Qi | 4 | 74 | 18.36 |
| Xiaoyan Xi | 5 | 0 | 1.35 |