Stochastic methods for image mining and data quality (DAQUAL)
Modern remote sensing images are of an increasing quality, in terms of spatial and temporal resolution, spectral quality and variety of sensor types. Despite this growth, there is a limit to the precision, resulting in uncertainty. The topics of uncertainty are changing, though, as new questions are being posed and different information is collected as compared to images collected in the past. This research wishes to address this field: what uncertainty is present, how can we best address this in a quantitative way and how is this relevant for various application fields. Stochastic, i.e. probabilistic and statistical methods are of a general help in this sense. They are being combined with aspects of artificial intelligence, like fuzzy logic, and with mathematical methods.
| Research theme | Stochastic methods for image mining and data quality (DAQUAL) |
| Research group leader | Prof. Dr. Ir. A. Stein |
| Keywords | Geostatistics, remote sensing data mining, data quality |
| ITC theme code | 3 310 010 |
DAQUAL - Annual report 2008 (13 kB)