| Item type |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2011-01-24 |
| タイトル |
|
|
タイトル |
Improved Contextual Classifiers of Multispectral Image Data |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
contextual classification |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
multispectral image |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
remote sensing |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
probabilistic relaxation |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 著者 |
WATANABE, Takashi
SUZUKI, Hitoshi
TANBA, Sumio
YOKOYAMA, Ryuzo
|
| 著者(機関) |
|
|
値 |
Faculty of Engineering, Iwate University |
| 著者(機関) |
|
|
値 |
Product Engineering Department, NEC Corporation |
| 著者(機関) |
|
|
値 |
Faculty of Engineering, Iwate University |
| 著者(機関) |
|
|
値 |
Faculty of Engineering, Iwate University |
| 登録日 |
|
|
日付 |
2011-01-24 |
| 書誌情報 |
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
巻 E77-A,
号 9,
p. 1445-1450,
発行日 1994-09-01
|
| ISSN |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
0916-8508 |
| Abstract |
|
|
内容記述タイプ |
Other |
|
内容記述 |
Contextual classification of multispectral image data in remote sensing is discussed and concretely two improved contextual classifiers are proposed. The first is the extended adaptive classifier which partitions an image successively into homogeneously distributed square regions and applies a collective classification decision to each region. The second is the accelerated probabilistic relaxation which updates a classification result fast by adopting a pixelwise stopping rule. The evaluation experiment with a pseudo LANDSAT multispectral image shows that the proposed methods give higher classification accuracies than the compound decision method known as a standard contextual classifier. |
| 出版者 |
|
|
出版者 |
The Institute of Electronics, Information and Communication Engineers |
| 権利 |
|
|
権利情報 |
copyright©1994 IEICE |
| 著者版フラグ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
tfeccs-ve77-an9p1445-1450.pdf (434.8 kB)
