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STUDY OF AUTOMATIC IMAGE RECTIFICATION AND REGISTRATION OF SCANNED HISTORICAL AERIAL PHOTOGRAPHS

机译:扫描历史空中照片自动图像整流和注册的研究

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Historical aerial photographs directly provide good evidences of past times. The Research Center for Humanities and Social Sciences (RCHSS) of Taiwan Academia Sinica has collected and scanned numerous historical maps and aerial images of Taiwan and China. Some maps or images have been geo-referenced manually, but most of historical aerial images have not been registered since there are no GPS or IMU data for orientation assisting in the past. In our research, we developed an automatic process of matching historical aerial images by SIFT (Scale Invariant Feature Transform) for handling the great quantity of images by computer vision. SIFT is one of the most popular method of image feature extracting and matching. This algorithm extracts extreme values in scale space into invariant image features, which are robust to changing in rotation scale, noise, and illumination. We also use RANSAC (Random sample consensus) to remove outliers, and obtain good conjugated points between photographs. Finally, we manually add control points for registration through least square adjustment based on collinear equation. In the future, we can use image feature points of more photographs to build control image database. Every new image will be treated as query image. If feature points of query image match the features in database, it means that the query image probably is overlapped with control images. With the updating of database, more and more query image can be matched and aligned automatically. Other research about multi-time period environmental changes can be investigated with those geo-referenced temporal spatial data.
机译:历史空中照片直接提供过去时期的良好证据。台湾学术研究中心(RCHS)研究中心是众多历史地图和中国的历史地图和空中形象。一些地图或图像手动参考,但大多数历史空中图像都没有注册,因为过去没有GPS或IMU数据进行辅助。在我们的研究中,我们通过SIFT(尺度不变特征变换)开发了匹配历史空中图像的自动过程,用于通过计算机视觉处理大量图像。 SIFT是图像特征提取和匹配最受欢迎的方法之一。该算法将刻度空间中的极值提取为不变的图像特征,这对于在旋转尺度,噪声和照明中改变的强大。我们还使用Ransac(随机样本共识)来删除异常值,并在照片之间获取好的共轭点。最后,我们通过基于共线方程手动通过最小二乘调节添加控制点。将来,我们可以使用更多照片的图像特征点来构建控制图像数据库。每个新图像都将被视为查询图像。如果查询图像的特征点匹配数据库中的功能,则表示查询图像可能与控制图像重叠。随着数据库的更新,可以匹配越来越多的查询映像并自动对齐。可以使用那些地理参考的时间空间数据调查关于多时间段环境变化的其他研究。

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