Enhancement Algorithm for Low-lighting Images Based on Physical Model and Boundary Constraint

CHEN Yong; ZHAN Di; LIU Huanlin

doi:10.11999/JEIT170267

Volume 39 Issue 12

Dec. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(12): 2962-2969

CHEN Yong, ZHAN Di, LIU Huanlin. Enhancement Algorithm for Low-lighting Images Based on Physical Model and Boundary Constraint[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2962-2969. doi: 10.11999/JEIT170267

Citation:

CHEN Yong, ZHAN Di, LIU Huanlin. Enhancement Algorithm for Low-lighting Images Based on Physical Model and Boundary Constraint[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2962-2969. doi: 10.11999/JEIT170267

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Enhancement Algorithm for Low-lighting Images Based on Physical Model and Boundary Constraint

doi: 10.11999/JEIT170267

(Key Laboratory of Industrial Internet of Things and Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

Funds:

The National Natural Science Foundation of China (60975008), Chongqing Graduate Student Science Research Innovation Foundation (CYS17235)

Received Date: 2017-03-29
Rev Recd Date: 2017-09-18
Publish Date: 2017-12-19

Abstract

Abstract

The aim of this paper is to achieve a low-lighting image enhancement method by using the similarity between fog image and inverted low illumination image. The transmittance estimation of the pseudo-fog image is estimated by the improved boundary constraint, and then it is optimized. Based on the formation principle of pseudo fog, the light intensity of pseudo fog map is estimated by using the brightness component of low illumination image. The enhanced pseudo fog image is reversed to obtain the enhanced low illumination image. Extensive experimental results using natural low-lighting images indicate that the proposed method perform better than contemporary algorithms in terms of several metrics, including the intensity, the contrast. The proposed algorithm can effectively suppress the wrong phenomenon caused by enhanced with low complexity.
- Low-lighting image enhancement,
- Pseudo-fog image,
- Boundary constraint,
- Physical model

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References(27)

References

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