TR2017-114

Fusion of multi-angular aerial Images based on epipolar geometry and matrix completion


    •  Ma, Y., Liu, D., Mansour, H., Kamilov, U., Taguchi, Y., Boufounos, P.T., Vetro, A., "Fusion of multi-angular aerial Images based on epipolar geometry and matrix completion", IEEE International Conference on Image Processing (ICIP), DOI: 10.1109/ICIP.2017.8296471, September 2017.
      BibTeX TR2017-114 PDF
      • @inproceedings{Ma2017sep,
      • author = {Ma, Yanting and Liu, Dehong and Mansour, Hassan and Kamilov, Ulugbek and Taguchi, Yuichi and Boufounos, Petros T. and Vetro, Anthony},
      • title = {Fusion of multi-angular aerial Images based on epipolar geometry and matrix completion},
      • booktitle = {IEEE International Conference on Image Processing (ICIP)},
      • year = 2017,
      • month = sep,
      • doi = {10.1109/ICIP.2017.8296471},
      • url = {https://www.merl.com/publications/TR2017-114}
      • }
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  • Research Area:

    Digital Video

We consider the problem of fusing multiple cloud-contaminated aerial images of a 3D scene to generate a cloud-free image, where the images are captured from multiple unknown view angles. In order to fuse these images, we propose an end-to-end framework incorporating epipolar geometry and low-rank matrix completion. In particular, we first warp the multi-angular images to single-angle ones based on the estimated fundamental matrices that relate the multi-angular images according to their projective relations to the 3D scene. Then we formulate the fusion process of the warpped images as a low-rank matrix completion problem where each column of the matrix corresponds to a vectorized image with missing entries corresponding to cloud or occluded areas. Results using DigitalGlobe high spatial resolution images demonstrate that our algorithm outperforms existing approaches.

 

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