Abstract
Image fusion is the combination of two or more different images to form a new image by using a certain algorithm. The aim of image fusion is to integrate complementary data in order to obtain more and better information about an object or a study area than can be derived from single sensor data alone. Image fusion can be performed at three different processing levels which are pixel level, feature-level and decision-level according to the stage at which the fusion takes place. This paper explores the major remote sensing data fusion techniques at feature and decision levels implemented as found in the literature. It compares and analyses the process model and characteristics including advantages, limitations and applicability of each technique, and also introduces some practical applications. It concludes with a summary and recommendations for selection of suitable methods.
| Original language | English |
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| Title of host publication | Proceedings of the ISPRS Commission VII Symposium |
| Subtitle of host publication | Remote Sensing: From Pixels to Processes, Enschede, The Netherlands, May 8-11, 2006 |
| Editors | Andrew Skidmore, Norman Kerle |
| Place of Publication | Enschede, The Netherlands |
| Publisher | International Institute for Geo-Information Science and Earth Observation |
| Number of pages | 5 |
| Publication status | Published - 2006 |
| Event | ISPRS Commission VII Symposium 2006: Remote Sensing: From Pixels to Processes - Enschede, Netherlands Duration: 8 May 2006 → 11 May 2006 https://www.isprs.org/proceedings/XXXVI/part7/ |
Conference
| Conference | ISPRS Commission VII Symposium 2006 |
|---|---|
| Country/Territory | Netherlands |
| City | Enschede |
| Period | 8/05/06 → 11/05/06 |
| Internet address |
Keywords
- ADLIB-ART-1324
- EOS