Volume 18, Issue 3, November 2016, Pages 880–884
Nada Jasim Habeeb1
1 Technical College of Management, Middle Technical University, Iraq
Original language: English
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Many researchers in image and video processing field test the effectiveness of the proposed or existing methods depended on the assumption that the brightness or illumination in scene is static among all sequenced images or frames. So they used synthetic dataset with frames contain approximately static blurriness degrees. This is not practical in the real world. In this paper, a method of generating synthetic blurred video dataset with frames containing different blur variances to solve this problem. The result showed that the proposed algorithm has ability to produce useful blurred dataset with having different blurriness values.
Author Keywords: Blur, synthetic dataset, random number generator, averaging filter.
Nada Jasim Habeeb1
1 Technical College of Management, Middle Technical University, Iraq
Original language: English
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Many researchers in image and video processing field test the effectiveness of the proposed or existing methods depended on the assumption that the brightness or illumination in scene is static among all sequenced images or frames. So they used synthetic dataset with frames contain approximately static blurriness degrees. This is not practical in the real world. In this paper, a method of generating synthetic blurred video dataset with frames containing different blur variances to solve this problem. The result showed that the proposed algorithm has ability to produce useful blurred dataset with having different blurriness values.
Author Keywords: Blur, synthetic dataset, random number generator, averaging filter.
How to Cite this Article
Nada Jasim Habeeb, “Generating Blurred Dataset with Different Blurriness Degree Variances,” International Journal of Innovation and Applied Studies, vol. 18, no. 3, pp. 880–884, November 2016.
