以生物序列演算法進行UAV影像幾何校正控制點匹配新型模式之探索性研究

Exploratory Research of a Novel GCPs Matching Model for UAV Image Geometric Correction through Biological Sequence Algorithms

10.6574/JPRS.202109_26(3).0002

雷祖強(Tsu-Chiang Lei)；吳仕傑(Shih-Chieh Wu)；李哲源(Che-Yuan Li)；曾國欣(Guo-Shin Tzeng)

影像幾何校正 ； 生物序列分析 ； 自動化匹配 ； 無人載具 ； Image Geometric Correction ； Biological Sequence Algorithms ； GCPs Automatically Matching Procedure

航測及遙測學刊

26卷3期（2021 / 09 / 01）

143 - 162

繁體中文

本研究開發了一種新穎的半自動地面控制點（Ground Control Points, GCPs）匹配模型來解決UAV影像校正問題。我們使用生物序列演算法（Biological sequence algorithms）為概念來進行影像匹配程序，其概念則是透過Needleman-Wunsch algorithm（NWA）的全局特徵對齊技術，匹配兩個影像（基準影像和待校正影像）中的物件對象，在識別成功匹配的物件對象後，再利用Smith-Waterman algorithm（SWA）的局部特徵對齊技術，從匹配成功的物件對象中提取GCPs，最後，再使用多項式模型方法對於所提出GCPs進行幾何校正與價值評估。研究的案例成果顯示，除了可從本研究中所使用的影像中自動提取適當的GCPs之外，而影像進行幾何校正後，經由人工刪去殘差值大於1個單位的控制點後，剩餘控制點的RMSE（均方根誤差）值為0.52418，可證明本研究之方法未來可適用於高解析度影像之GCPs校正問題。

This study developed a novel semi-automatic ground control point (GCPs) matching model, which can resolve the problem of GCPs matching when carrying out geometric correction for two UAV images. This research methods utilized the concept of the Biological Sequence Algorithms (BSA) to present image matching procedures. More specifically, the Needleman-Wunsch algorithm (NWA) was first used as a global object alignment technique to match objects in the two images (corrected image and uncorrected image). After identifying the successfully matched objects, the Smith-Waterman Algorithm (SWA) was used as a local features alignment technique to extract the GCPs from matched objects. Finally, the polynomial model method was applied for geometric correction and assessment of the proposed model. Finally, the results of this case showed that appropriate GCPs were automatically extracted from the images used in this study. After the geometric correction, the RMSE (Root- Mean-Square Error) value was 0.52418, indicating the method of this study is appropriate for the application on high-resolution images.

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