A self-adaptive Contrast Enhancement Method Based on Gradient and Intensity Histogram for Remote Sensing Images
Tieqiao Chen, Jiahang Liu, Xiuqin Su, Jia Liu, Feng Zhu, Yihao Wang
Available Online July 2016.
- https://doi.org/10.2991/iccia-17.2017.53How to use a DOI?
- Contrast enhancement, remote sensing image, self-adaptive algorithm, gradient and intensity histogram.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/iccia-17.2017.53 ID - Chen2016/07 ER -