Name
Abstract | ||
|---|---|---|
This paper addresses the problem of defining a similarity measure between an observed Gaussian image and a binary image constructed from a cartographic database. The main idea is to assume that the binary image has been obtained by thresholding an unobserved Gaussian image correlated with the observed image. The proposed statistical model is then used to estimate its unknown parameters using the maximum likelihood method. The paper discusses a possible application to change detection between a cartographic vector data base and an optical image. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IGARSS.2009.5418268 | Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009 |
Keywords | Field | DocType |
geophysical image processing,optical images,visual databases,Gaussian image,binary image,cartographic vector database,change detection,correlation coefficient,image databases,maximum likelihood method,optical images,statistical model,Image databases,change detection,correlation coefficient,maximum likelihood estimation | Correlation coefficient,Computer vision,Change detection,Similarity measure,Feature detection (computer vision),Pattern recognition,Computer science,Binary image,Gaussian,Artificial intelligence,Statistical model,Thresholding | Conference |
Volume | ISSN | ISBN |
2 | 2153-6996 | 978-1-4244-3395-7 |
Citations | PageRank | References |
1 | 0.42 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jean-Yves Tourneret | 1 | 835 | 64.32 |
| Vincent Poulain | 2 | 22 | 2.40 |
| Marie Chabert | 3 | 132 | 22.50 |
| Jordi Inglada | 4 | 82 | 6.90 |