EPJ Web Conf.
Volume 224, 2019IV International Conference “Modeling of Nonlinear Processes and Systems” (MNPS-2019)
|Number of page(s)||5|
|Section||Machine Learning, Artificial Intelligence and High-Performance Computing|
|Published online||09 December 2019|
Modified Local and Global Contrast Enhancement Algorithm for Color Satellite Image
Moscow State Technological University “STANKIN”, RU-127055, Moscow, Russia
2 Don Sate Technical University, RU-344000, Rostov-on-Don, Russia
* e-mail: email@example.com
Published online: 9 December 2019
The quality of remotely sensed satellite images depends on the reflected electromagnetic radiation from the earth’s surface features. Lack of consistent and similar amounts of energy reflected by different features from the earth’s surface results in a poor contrast satellite image. Image enhancement is the image processing of improving the quality that the results are more suitable for display or further image analysis. In this paper, we present a detailed model for color image enhancement using the quaternion framework. We introduce a novel quaternionic frequency enhancement algorithm that can combine the color channels and the local and global image processing. The basic idea is to apply the α-rooting image enhancement approach for different image blocks. For this purpose, we split image in moving windows on disjoint blocks. The parameter alfa for every block and the weights for every local and global enhanced image driven through optimization of measure of enhancement (EMEC). Some presented experimental results illustrate the performance of the proposed approach on color satellite images in comparison with the state-of-the-art methods.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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