Application of maximum likelihood classification Based on minimal risk in crop interpretation
Yubin Song, Xiufeng Yang, Yancang Wang, Zihui Zhao, Xuhong Ren, Longfang Duan
Available Online December 2015.
- https://doi.org/10.2991/icmmcce-15.2015.516How to use a DOI?
- classification,minimal risk,crop, interpretation.
- 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.
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 -