Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015

Application of maximum likelihood classification Based on minimal risk in crop interpretation

Authors
Yubin Song, Xiufeng Yang, Yancang Wang, Zihui Zhao, Xuhong Ren, Longfang Duan
Corresponding Author
Yubin Song
Available Online December 2015.
DOI
https://doi.org/10.2991/icmmcce-15.2015.516How to use a DOI?
Keywords
classification,minimal risk,crop, interpretation.
Abstract
In crop interpretation by remote sensing, Gray distribution of crop is overlapped in some intervals. The non-target crops fall into the target crop, which would greatly increase the workload in post classification. To reduce these classification errors, and improve accuracy of clarification, maximum likelihood classification based on minimal risk is used. And the relationship between extraction rate and accuracy were analyzed. Experiments show that this method can improve the accuracy of extracting target crops, reduce the workload of the post classification, and improve efficiency.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Yubin Song
AU  - Xiufeng Yang
AU  - Yancang Wang
AU  - Zihui Zhao
AU  - Xuhong Ren
AU  - Longfang Duan
PY  - 2015/12
DA  - 2015/12
TI  - Application of maximum likelihood classification Based on minimal risk in crop interpretation
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.516
DO  - https://doi.org/10.2991/icmmcce-15.2015.516
ID  - Song2015/12
ER  -