A self-adaptive Contrast Enhancement Method Based on Gradient and Intensity Histogram for Remote Sensing Images

DOI

10.2991/iccia-17.2017.53How to use a DOI?

Keywords

Contrast enhancement, remote sensing image, self-adaptive algorithm, gradient and intensity histogram.

Abstract

This paper proposes an efficient method to modify gradient and intensity histograms (GIH) for contrast enhancement, which plays an important role in remote sensing image processing and information extraction. First, a self-adaptive algorithm is used to flatten the shape of GIH of input image according to standard deviation of GIH. Then, the standard lookup table-based histogram equalization procedure is applied to get well enhanced image. Experimental results, using various remote sensing images, show that the proposed method generates enhanced images with more information and higher visual quality, compared with several conventional methods.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Tieqiao Chen
AU  - Jiahang Liu
AU  - Xiuqin Su
AU  - Jia Liu
AU  - Feng Zhu
AU  - Yihao Wang
PY  - 2016/07
DA  - 2016/07
TI  - A self-adaptive Contrast Enhancement Method Based on Gradient and Intensity Histogram for Remote Sensing Images
BT  - Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
PB  - Atlantis Press
SP  - 312
EP  - 316
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-17.2017.53
DO  - 10.2991/iccia-17.2017.53
ID  - Chen2016/07
ER  -