Automatic Tie-point Extraction Based on Multiple-image Matching and Bundle Adjustment of Large Block of Oblique Aerial Images

doi:10.11947/j.AGCS.2017.20160571

Abstract

Abstract: Due to advantages such as ease of interpretation, completeness through mitigation of occluding areas, as well as system accessibility, the aerial oblique images have found their place in numerous civil applications. However, for these applications high quality orientation data are essential. A fully automatic tie-point extraction procedure is developed to precisely orient the large block of oblique aerial images, in which a refined ASIFT algorithm and a window-based multiple-viewing image matching (WMVM) method are combined. In this approach, the WMVM method is based on the concept of multi-image matching guided from object space and allows reconstruction of 3D objects by matching all available images simultaneously, and a square correlation window in the reference image can be correlated with windows of different size, shape and orientation in the search images.Then another key algorithms, i.e. the combined bundle adjustment method with gross-error detection & removal algorithm, which can be used for simultaneously orient the oblique and nearly-vertical images will be presented. Finally, through the experiments by using real oblique images over several test areas, the performance and accuracy of the proposed method is studied and presented.

Key words: oblique aerial photos, bundle adjustment, affine invariant feature detector, feature extraction, multiple-image matching

CLC Number:

P237

ZHANG Li, AI Haibin, XU Biao, SUN Yushan, DONG Youqiang. Automatic Tie-point Extraction Based on Multiple-image Matching and Bundle Adjustment of Large Block of Oblique Aerial Images[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(5): 554-564.

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