Journal of Geo-information Science >
Cultivated Land Extraction Based on Image Region Division and Scale Estimation
Received date: 2018-01-09
Request revised date: 2018-04-09
Online published: 2018-07-13
Supported by
National Natural Science Foundation of China, No.41371347, 41671369;Open Fund of Twenty First Century Areospace Technology Company Limitied. No.21AT-2016-07;Fundamental Research Funds for Central Universities
Copyright
Influenced by scale effect, different objects have different spatial and attribute scales, so there is no one set of segmentation parameters can suit all objects in the same image. However, classifying similar objects into same region, and then setting optimal segmentation parameters for different regions can improve the overall segmentation accuracy of the images effectively. In cultivated land extraction, it is critical to have clear and continuous boundary for the segmented plots. This paper presents a cultivated land extraction method combining image region division and segmentation parameters estimation. Temperature inversion was used to divide the image into different regions, of which the types of covered objects are different or the growths of crops are different. Next, regional image segmentation is performed for different regions. Since different object's inherent spatial scales are different, so different regional images' optimal segmentation parameters are also different. The optimal segmentation parameters of the image can be estimated to a certain level by analyzing the characteristics of the image space quantitatively. Compared with other segmentation parameter optimization selection methods, this method can be accurately and quickly positioned, and has a higher efficiency. Next, estimated segmentation parameters were used in the process of cultivated land segmentation by using edge restraint watershed segmentation algorithm. Edge restraint watershed segmentation algorithm uses the canny operator for the post-processing of the watershed segmentation algorithm. The boundary of the canny operator is used to constrain the consolidation process. The experimental result shows that the method proposed in this paper can set segmentation parameters for different regions quickly and accurately. Compared with other segmentation methods, this propose method has a quite clearer and more continuous block boundaries and the boundary fragmentation problem is greatly relieved.
ZHOU Wen , MING Dongping , YAN Pengfei . Cultivated Land Extraction Based on Image Region Division and Scale Estimation[J]. Journal of Geo-information Science, 2018 , 20(7) : 1014 -1025 . DOI: 10.12082/dqxxkx.2018.180076
Fig. 1 Flow chart of arable land plots segmentation technology图1 耕地地块分割技术流程图 |
Fig. 2 Temperature inversion flow chart图2 温度反演流程图 |
Fig. 3 Experimental data图3 实验数据 |
Fig. 4 Temperature inversion data图4 温度反演数据 |
Fig. 5 Region division result of Beijing No.2 satellite data image图5 北京二号影像分区结果 |
Fig. 6 Regional experimental image图6 区域试验影像 |
Fig. 7 Mean local variance and its related parameters for bare land image图7 裸地影像平均局部方差及其相关参数 |
Fig. 8 Mean local variance and its related parameters for crop land image图8 农田影像平均局部方差及其相关参数 |
Fig. 9 Histogram of local variance of bare land image图9 裸地影像局部标准差直方图 |
Fig. 10 Histogram of local variance of crop land image图10 农田影像局部标准差直方图 |
Fig. 11 Evaluation of segmentation results of bare land image图11 裸地试验区分割评价 |
Fig. 12 Evaluation of segmentation results of crops image图12 农田试验区边缘约束分水岭分割评价 |
Fig. 13 Comparison of edge-constrained watershed and multi-resolution segmentation result图13 边缘约束的分水岭与多分辨率分割结果对比 |
Fig. 14 Comparison of edge-constrained watershed and multi-resolution segmentation result图14 边缘约束的分水岭与多分辨率分割结果对比 |
Tab. 1 Comparison of two segmentation methods in bare land image表1 裸地影像2种分割方法对比 |
最佳评价结果 | 边缘约束分水岭分割 | 多分辨率分割 | |
---|---|---|---|
基元数 | 1900284 | 2388 | |
Ui | 2029.231 | 353.086 | |
Vi | -0.042009 | 0.119191 | |
A(i) | 0.021250899 | -0.058179414 |
Tab. 2 Comparison of two segmentation methods in bare crops image表2 农田试验区影像2种分割方法对比 |
最佳评价结果 | 边缘约束分水岭分割 | 多分辨率分割 |
---|---|---|
基元数 | 1840250 | 9120 |
Ui | 927.049 | 127.009 |
Vi | -0.048007 | 0.000182 |
A(i) | 0.024542846 | 0.003845729 |
The authors have declared that no competing interests exist.
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