| タイトル | Iterative Bayesian Classification In Polarimetric SAR |
| 著者（英） | Van Zyl, Jakob J.; Burnette, Charles F. |
| 著者所属（英） | Jet Propulsion Lab., California Inst. of Tech. |
| 発行日 | 1992-09-01 |
| 言語 | eng |
| 内容記述 | In improved scheme for Bayesian classification of picture elements in polarimetric synthetic-aperture radar image of terrain, priori probability that given picture element belongs to given class, adjusted according to spatial variation of statistical properties of image data. Accuracy increases dramatically in first few iterations. Scheme involves sequence of classifications. In first, a priori probability that element belongs to class taken to be constant over the whole image. In subsequent classifications, adaptive a priori probabilities calculated for each picture element. |
| NASA分類 | MATHEMATICS AND INFORMATION SCIENCES |
| レポートNO | 92B10567
NPO-18308 |
| 権利 | No Copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/331952 |
