鲁 恒,李龙国,贺一楠,庄文化,蔡诗响,何 敬.考虑地形特征的无人机影像分区域加权平差拼接方法[J].农业机械学报,2015,46(9):296-301.
Lu Heng,Li Longguo,He Yinan,Zhuang Wenhua,Cai Shixiang,He Jing.Method of UAV Image Mosaic Based on Weighted Adjustment Considering Terrain Feature[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(9):296-301.
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考虑地形特征的无人机影像分区域加权平差拼接方法   [下载全文]
Method of UAV Image Mosaic Based on Weighted Adjustment Considering Terrain Feature   [Download Pdf][in English]
投稿时间:2015-06-23  
DOI:10.6041/j.issn.1000-1298.2015.09.043
中文关键词:  无人机影像 分区域 加权平差 影像拼接 地形特征
基金项目:国家自然科学基金青年基金资助项目(51209153、41301021)、2014年基础测绘科技计划资助项目、数字制图与国土信息应用工程国家测绘地理信息局重点实验室开放基金资助项目(DM2014SC02)和国土资源部地学空间信息技术重点实验室开放基金资助项目(KLGSIT2015-04)
作者单位
鲁 恒 四川大学 
李龙国 四川大学 
贺一楠 北卡罗来纳大学 
庄文化 四川大学 
蔡诗响 四川大学 
何 敬 成都理工大学 
中文摘要:无人机遥感手段以其方便、快捷、成本低、可云下飞行的优势正越来越多地应用于农情信息的获取。为了解决无人机影像的数量多、畸变大、影像拼接过程中产生大量累积误差等问题,对拼接过程中如何减少误差累积进行了研究。首先,根据记录影像匹配过程中心点位置计算大致的匹配区域。然后,进行区域网概略计算,列出误差方程。对不同地形特征区域影像赋予权值,进行分区域加权平差。最后,利用3条航带的无人机影像分别对所提方法和直接拼接法进行了实验对比。实验结果表明:所提方法拼接后错位和鬼影现象减少了12%,拼接效率提高了15%,拼接后获得的面积扩大了8%。
Lu Heng  Li Longguo  He Yinan  Zhuang Wenhua  Cai Shixiang  He Jing
Sichuan University,Sichuan University,University of North Carolina,Sichuan University,Sichuan University and Chengdu University of Technology
Key Words:UAV images Regional separation Weighted adjustment Image mosaic Terrain feature
Abstract:The development of precision agriculture demands high accuracy and efficiency of cultivated land information extraction. Due to the low spatial resolution of satellite remote sensing images, it is difficult to identify cultivated land of small areal extent in critical regions; this requires image data of high spatial resolution for specific or general cases. Simultaneously, unmanned aerial vehicle (UAV) has been increasingly used for natural resource applications in recent years as a result of its greater availability, the miniaturization of sensors, and the ability to deploy UAV relatively quickly and repeatedly at low altitudes. In order to solve the problem of large quantity, distortion and accumulated error in the process of UAV image mosaic, how to reduce accumulated error efficiently was researched. First of all, matching area was calculated according to the record center points in process of matching. Then error equation was listed based on the results of regional network summary calculation. Next, images were given weight value by different terrain features areas to conduct area weighted adjustment. Finally, mosaic experiments were completed by the proposed method and direct mosaic method based on three flight strips UAV images. The experimental results show that the ghost and dislocation phenomenon was decreased by 12%, mosaic efficiency was increased by 15%, and the area after mosaic was expanded by 8%. The method can mosaic UAV images better at error control and efficiency.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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