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

DOI

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - 10.2991/icmmcce-15.2015.516
ID  - Song2015/12
ER  -