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https://ello.co/7rostnimisspi/post/b9gusvcjr-nn03dn_gsvwg
https://colab.research.google.com/drive/1uxZQK1s6R-Hb260hs5yXbaLb7Gxu5TL7

Next, the camera rotates in the remaining sense. By rotating the camera further, we can get images of all of the objects. For example, if we rotate the camera 135° or so, we can get the image of all the objects. This is the process we apply to the previously got images. An example of the output of the algorithm is given in figure 3.2.

fig. 3.2.4 Two-frame image output of K-p algorithm under noise-free conditions (a) and under noisy conditions.

The reason why we chose this particular technique is that it does not require any post-processing. Moreover, it is very fast. A paper discussing the theoretical basis of the K-p algorithm was published in 1980 [25]. Another paper discussing the practical issues of the algorithm was published in 1982 [26]. The latest version of the algorithm is available here:

3.3.5 Conclusion

Detecting aircraft from imagery without access to an accurate reference point is challenging. One of the methods is using the color images and geometric techniques. This article presents some of the techniques to estimate altitude and azimuth of aircraft and a complex scene from a single image. Although the presented algorithms are not perfect, they can be used as a rough initial guess for the desired output and can be applied to scenes in which aircraft are not clearly recognizable. Moreover, the presented algorithms can be used as a basis for more complicated methods such as measuring the altitude of cloud top from images. In the future we intend to use all of these algorithms to calculate a cloud top altitude from a single image (with no knowledge of the altitude) using a simple tip-tilt algorithm.

References

1.

Anderson, M.L., Moyer, C.R., Lewis, K.P., & Ashburn, T.W. (2007). Analysis of passive night time imagery reveals active aircraft or their wake turbulence. The Journal of the Acoustical Society of America, 120(5), 2497-2505.

2.

Bandyopadhyay, S., Yuan, J., & Liu, X. (2013, Aug). An iterative method for aircraft detection in videos: Application to a UAV landing video. In ICES 2013, 2013 International Conference on Environmental Systems (pp. 119-124). IEEE.

3.
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