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Enhancement of Infrared Image Based on the Retinex Theory

Authors: Ying, Li; Changzhi, Hou; Fu, Tian; Hongli, Yu; Lei, Guo; Guizhi, Xu; Xueqin, Shen; +1 Authors

Enhancement of Infrared Image Based on the Retinex Theory

Abstract

The infrared imaging technique can be used to image the temperature distribution of the body. It's hopeful to be applied to the diagnosis and prediction of many diseases. Image processing is necessary to enhance the original infrared images because of the blurring. In this paper, the image enhancement technique based on the Retinex theory is studied. The algorithms such as Frackle-McCann algorithm, McCann99 algorithm, single-scale Retinex algorithm and multi-scale Retinex algorithm are applied to the enhancement of gray infrared image. The acceptable results are obtained and compared.

Related Organizations
Keywords

Diagnostic Imaging, Spectrophotometry, Infrared, Infrared Rays, Thermography, Image Interpretation, Computer-Assisted, Humans, Reproducibility of Results, Computer Simulation, Models, Biological, Sensitivity and Specificity

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
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