| Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
|---|---|---|
| Article Number | 03042 | |
| Number of page(s) | 5 | |
| Section | Digital Signal and Image Processing | |
| DOI | https://doi.org/10.1051/matecconf/201817303042 | |
| Published online | 19 June 2018 | |
Background Self-adaptive Weakly-monotonic Averaging Image Reduction Operator
School of Computer Science Xi’an ShiYou University, 710065, Shannxi, China
* Corresponding author: Haiyang_xia@qq.com
Image reduction can simplify the raw image while preserve the structure feature and details information of pictures. Traditional monotonic averaging-based image reduction operator usually lose the detail features of the raw image after reduction. Recent proposed weakly-monotone image reduction algorithm need to specify the background colour manually in the image reduction process, if the background colour of the image to be reduced is not consistent with the former specified colour, this method does not work as expect. For filling this research gap, a new background adaptive weakly-monotonic averaging image reduction operator which can identify the background and adjust the weight according to the pixel distribution of the image was proposed in this paper. The experiment shows that compared with the previous image reduction operator, it has a better applicability and robustness.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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