#219:
R. Aktar,
V. B. S. Prasath,
H. Aliakbarpour,
U. Sampathkumar,
G. Seetharaman, and
K. Palaniappan
Proc. IEEE Applied Imagery Pattern Recognition Workshop (AIPR),
pgs. 1-7,
2016
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In this work we consider haze removal from videos using the dark channel prior approach with applications wide area motion imagery (WAMI). Most of the haze-free non-sky outdoor images contain at least one color channel with average intensity close to zero; this channel is called dark channel and provides a good estimate of the transmission of haze which is used to remove haze from image. By utilizing neighborhood consistency in temporal direction of videos we apply haze removal algorithm sequentially. Once the haze-free images are produced, we register them in order to generate mini-mosaics and apply poison blending to remove seam effect from the mini-mosaics. Experimental results on synthetic image sequences and WAMI indicate we obtain good haze-free and mosaiced results.
@inproceedings{Rumana:Hazeremoval-WAMI-AIPR-2016,
author = "R. Aktar and V. B. S. Prasath and H. Aliakbarpour and U. Sampathkumar and G. Seetharaman and K. Palaniappan",
title = "Video haze removal and Poisson blending based mini-mosaics for wide area motion imagery",
year = 2016,
journal = "Proc. IEEE Applied Imagery Pattern Recognition Workshop (AIPR)",
publisher = "IEEE",
pages = "1-7",
month = "Oct",
keywords = "haze removal, blending, mosaicing, wami",
url = "https://www.researchgate.net/publication/319169936_Video_haze_removal_and_poisson_blending_based_mini-mosaics_for_wide_area_motion_imagery"
}
R. Aktar, V. B. S. Prasath, H. Aliakbarpour, U. Sampathkumar, G. Seetharaman, and K. Palaniappan. Video haze removal and Poisson blending based mini-mosaics for wide area motion imagery. Proc. IEEE Applied Imagery Pattern Recognition Workshop (AIPR), IEEE, pages 1-7, October 2016.
