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PMSR model for low illumination image enhancement
Author(s): Yong Li; Junping Wang; Gangming Liang; Jiajia Guo
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Paper Abstract

Enhancement of low illumination images is of great importance in poor imaging conditions. A new image enhancement model was proposed in this paper. The model divided an image into blocks and used the local standard deviation to design the center/surround filter and utilized amplitude compensation factor to compensate the shortage of logarithmic function in compressing the near-zero data’s amplitude. In addition, the amplitude compensation factor can suppress noise. At the same time, the normalized brightness can maintain the normal brightness region of the image while the brightness of the image is increased. In order to verify the performance of the proposed model, the proposed model and existing models are applied to image enhancement. To evaluate its performance in image enhancement, results are compared from the subjective and objective aspects. The experimental results show that the proposed model preserved the image details better and avoided the excessive enhancement of the normal brightness region.

Paper Details

Date Published: 10 April 2018
PDF: 8 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106152T (10 April 2018); doi: 10.1117/12.2303371
Show Author Affiliations
Yong Li, Xidian Univ. (China)
Junping Wang, Xidian Univ. (China)
Gangming Liang, Xidian Univ. (China)
Jiajia Guo, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

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