Abstract
In this paper, we propose a feature extraction method based on the Bhattacharyya distance for multimodal data. First, we estimate the classification error based on the Bhattacharyya distance between two multimodal classes that are approximated by a finite mixture of Gaussian distributions. Then we extract the features that minimize the estimated classification error. In order to find such features, we explore two search methods: sequential search and global search. Experiments show that the proposed feature extraction algorithm shows promising results.
| Original language | English |
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| Pages | 524-526 |
| Number of pages | 3 |
| Publication status | Published - 2001 |
| Event | 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) - Sydney, NSW, Australia Duration: 2001 Jul 9 → 2001 Jul 13 |
Other
| Other | 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) |
|---|---|
| Country/Territory | Australia |
| City | Sydney, NSW |
| Period | 01/7/9 → 01/7/13 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Earth and Planetary Sciences(all)