多视点乡村生产性景观最佳观赏位置测定
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摘要
为了提高乡村生产性景观最佳观赏位置的模糊性准确测定能力,提出一种基于多视点模糊跟踪检测的乡村生产性景观最佳观赏位置准确测定方法。采用景观图像的颜色分块区域标记方法进行乡村生产性景观最佳观赏位置自动成像处理,提取乡村生产性景观最佳观赏位置的暗原色先验特征信息,采用包络轮廓特征检测方法进行乡村生产性景观最佳观赏位置的边缘轮廓检测,有效增强了图像细节部分,提高了乡村生产性景观最佳观赏位置准确测定能力。仿真测试结果表明,采用该方法进行乡村生产性景观最佳观赏位置测定的自适应性能较好,图像信息饱和度较高。
In order to improve the fuzziness of the best ornamental position of the rural productive landscape,this paper presents an accurate measurement method of the best ornamental position of the rural productive landscape based on multi-view fuzzy tracking detection. The method of color segmentation and area marking of the landscape image is used to automatically image the best ornamental position of the rural productive landscape.The priori feature information of dark primary color was extracted from the best ornamental position of rural productive landscape, and the edge contour of the best ornamental position of rural productive landscape was detected by envelope contour feature detection method, which effectively enhanced the details of the image. Combined with the multi-view joint marker model, the boundary area of the rural productive landscape observation point can be detected, which can improve the ability to accurately determine the best ornamental location of the rural productive landscape. The simulation results show that this method has better adaptive performance and higher saturation of image information, and improves the accuracy of measurement.
In order to improve the fuzziness of the best ornamental position of the rural productive landscape,this paper presents an accurate measurement method of the best ornamental position of the rural productive landscape based on multi-view fuzzy tracking detection. The method of color segmentation and area marking of the landscape image is used to automatically image the best ornamental position of the rural productive landscape.The priori feature information of dark primary color was extracted from the best ornamental position of rural productive landscape, and the edge contour of the best ornamental position of rural productive landscape was detected by envelope contour feature detection method, which effectively enhanced the details of the image. Combined with the multi-view joint marker model, the boundary area of the rural productive landscape observation point can be detected, which can improve the ability to accurately determine the best ornamental location of the rural productive landscape. The simulation results show that this method has better adaptive performance and higher saturation of image information, and improves the accuracy of measurement.
引文
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[2]田韫智.美丽乡村建设背景下乡村景观规划分析[J].中国农业资源与区划,2016,37(09):229-232.
[3]姜婷婷,肖卫东,张翀,等.基于桑基图的时间序列文本可视化方法[J].计算机应用研究,2016,33(9):2683-2687.
[4]SHI Zhan,XIN Yu,SUN Yu'e et al.Task allocation mechanism for crowdsourcing system based on reliability of users.Journal of Computer Applications,2017,37(9):2449-2453.
[5]RUI L L,ZHANG P,HUANG H Q,et al.Reputation-based incentive mechanisms in crowdsourcing[J].Journal of Electronics&Information Technology,2016,38(7):1808-1815.
[6]ZHANG Y,JIANG C,SONG L,et al.Incentive mechanism for mobile crowdsourcing using an optimized tournament model[J].IEEE Journal on Selected Areas in Communications,2017,35(4):880-892.
[7]罗娜,李学国.图像去雾DCP算法的透射率容差参数修正[J].科技通报,2018,34(9):218-221.
[8]童强,李太君.复杂海面环境下船只边缘识别算法的改进[J].海南大学学报(自然科学版),2018,36(03):235-240.
[9]许妙忠,丛铭,万丽娟,等.视觉感受与Markov随机场相结合的高分辨率遥感影像分割法[J].测绘学报,2015,44(2):198-205.