Abstract
A supervised Mahalanobis distance fuzzy classifier (and the related fuzzy c-means clustering algorithm) requires the a priori selection of a weighting parameter called the fuzzy exponent. Guidance in the existing literature on an appropriate value is not definitive. This paper attempts to rigorously justify previous experimental findings on suitable values for this fuzzy exponent, using the criterion that fuzzy set memberships reflect class proportions in the mixed pixels of a remotely sensed image.
| Original language | Undefined/Unknown |
|---|---|
| Journal | Fuzzy Sets and Systems |
| Volume | 137 |
| Issue number | 2 |
| Pages (from-to) | 191-213 |
| Number of pages | 23 |
| ISSN | 0165-0114 |
| Publication status | Published - 2003 |
| Externally published | Yes |
Keywords
- Fuzzy classification
- Image Processing