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Enhancing infrared images via multi-resolution contrast stretching and adaptive multi-scale detail boosting

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Abstract

Infrared imaging technology has attracted numerous interests in military, security, transportation, etc. However, infrared images suffer from low contrast and blurry detail, limiting its application. To handle these issues, this paper presents a novel approach based on multi-resolution contrast stretching and adaptive multi-scale detail boosting. Specifically, the hybrid-spatial Gamma function can create the high-brightness feature map; multi-resolution analysis fully discovers the information in different screen resolutions for reconstructing the high-contrast feature map, i.e., the weighted adaptive limited contrast histogram equalization stretches the image’s approximate map and the hybrid Gamma function and histogram processes the detailed maps at different directions; the edge-preserving Gaussian blurring function can fully explore the details at different scale space for yielding the feature map with clearer details. Finally, the Laplace pyramid fuses different feature maps obeying the image-matching degree and average gradient to reconstruct pleasing visual images. Extensive experiments have shown that our method has an average increased by 13.0411, 1.6737, 23.3651, and 20.8085 in terms of average gradient (AG), information entropy (IE), enhancement by IE (EME), and image sharpness (IS), respectively, which is a proven approach for infrared image enhancement.

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Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Funding

This work was supported by the National Natural Science Foundation of China under grants (61866009, 62002082), the Guangxi Science and Technology Project (AB21220037), the Guangxi Natural Science Foundation under grants (2020GXNSFBA238014, 2020GXNSFAA297061), and the Innovation Project of Guangxi Graduate Education (YCBZ2022112).

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Authors and Affiliations

  1. School of Computer and Information Security, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, China

    Haoxiang Lu, Zhenbing Liu, Xipeng Pan, Rushi Lan & Wenhao Wang

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  1. Haoxiang Lu
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  2. Zhenbing Liu
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  3. Xipeng Pan
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  4. Rushi Lan
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  5. Wenhao Wang
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Contributions

HL contributed to the methodology, writing—original draft preparation and resources; ZL was involved in the funding acquisition and supervision; RL assisted in the funding acquisition and writing—review and editing; XP contributed to the funding acquisition and writing—review and editing; WW was involved in writing—review and editing.

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Correspondence to Zhenbing Liu.

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Lu, H., Liu, Z., Pan, X. et al. Enhancing infrared images via multi-resolution contrast stretching and adaptive multi-scale detail boosting. Vis Comput 40, 53–71 (2024). https://doi.org/10.1007/s00371-022-02765-y

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