Infrared image enhancement algorithm based on adaptive histogram segmentation
- 6 December 2017
- journal article
- research article
- Published by Optica Publishing Group in Applied Optics
- Vol. 56 (35), 9686-9697
- https://doi.org/10.1364/ao.56.009686
Abstract
Contrast enhancement plays a crucial role in infrared image pre-processing. Compared with the increasingly popular local-mapping enhancement methods, the global-mapping enhancement methods have a unique feature that reserves the thermal distribution information, which is vital in some temperature-sensitive applications. However, the main challenge of the global-mapping methods is how to enhance the contrast effectively without suffering from over-enhancement of the background and noise. To this end, we propose a novel global-mapping enhancement algorithm in this paper. First, the histogram is divided into several sub-histograms adaptively based on the heat conduction theory. By designing a metric called AHV, the background and non-background sub-histograms are distinguished, and then enhanced separately where more grayscales are allocated to non-background sub-histograms than background sub-histograms. Meanwhile, the property of the human visual system described by Weber’s law is also taken into consideration during the grayscale redistribution. The qualitative and quantitative comparisons with state-of-the-art methods on several databases demonstrate the advantages of our proposed method.Funding Information
- National Natural Science Foundation of China (NSFC) (61605146, 61503288)
- China Postdoctoral Science Foundation (2016M592385)
- Fundamental Research Funds for the Central Universities of China (2042016KF0017)
- Ministry of Education of the People’s Republic of China (MOE) (20120142110088)
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