A Robust Method for Mosaicking Sequence Images Obtained from UAV

At present, satellite and aerial remote sensing are common ways to collect data for territorial resources monitoring in most countries, but they are not effective, rapid and accurate enough. Compared with traditional ways of obtaining images, UAV based platform for photogrammetry and remote sensing is a more flexible and easy way to get high-resolution images with low cost. So building UAV based platforms is becoming a hot field throughout the whole world. However, there are also some problems with UAV images, e.g. the views of UAV images from UAV are smaller than those of traditional aerial images, so these images with small views should be pasted together in order to increase the visual field. Therefore, mosaicking UAV images is a critical task. The homographies between sequence images will be affected by the accumulated errors, which will lead to drifts of the position of each image in the mosaic. In this paper, we introduce a two-step optimization method for mosaicking UAV sequence images which can correct the homographies and improve the position of each image in the mosaic. Experimental results will also be presented.

[1]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[2]  William H. Press,et al.  Book-Review - Numerical Recipes in Pascal - the Art of Scientific Computing , 1989 .

[3]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[4]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[5]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[6]  J. G. Semple,et al.  Algebraic Projective Geometry , 1953 .

[7]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[8]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[9]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[10]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision (2nd ed) , 2003 .

[11]  Aníbal Ollero,et al.  Homography Based Kalman Filter for Mosaic Building. Applications to UAV position estimation , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[12]  Jinling Wang,et al.  Overlap Analysis of the Images from Unmanned Aerial Vehicles , 2010, 2010 International Conference on Electrical and Control Engineering.

[13]  O. Faugeras Three-dimensional computer vision: a geometric viewpoint , 1993 .

[14]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[15]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..