JOURNAL ARTICLE
High-greyscale X-ray film image enhancement algorithm based on brightness gain compensation and blackbody radiation chromatography remapping.
Published In: Insight: Non-Destructive Testing & Condition Monitoring, 2026, v. 68, n. 4. P. 267 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Sun, Mengyu; Li, Xiaoyan; Luo, Cheng; Wang, Peng; Tang, Lin; Li, Liangliang; Lv, Zhigang 3 of 3
Abstract
In order to solve the problem that ultra-8-bit high-greyscale X-ray film taken by a charge-coupled device (CCD) line scan camera cannot be directly visualised, an adaptive enhancement algorithm based on brightness gain compensation is proposed. Firstly, in order to solve the problem that a 12-bit image cannot be displayed, the prior eigenvalues of the image are extracted and a greyscale correction factor based on a feature prior coefficient is constructed. The greyscale distribution characteristics of the image are assessed by calculating its skewness to determine exposure levels, leading to the construction of a non-linear global mapping function for visualising 12-bit high-greyscale images. To address the significant information loss in high-greyscale images processed by existing pseudo-colour algorithms, this paper establishes a relationship between the spatial function of high greyscale and factors such as blackbody radiation, light wave wavelength, temperature and greyscale value. A red, green and blue (RGB) colour space is also designed based on brightness gain compensation to achieve pseudo-colour transformation of high-greyscale images. To verify the effectiveness of the proposed method, it is applied to various images, including a 12-bit X-ray image of an oil pipeline, a 24-bit digital radiography (DR) image of a steel pipe weld, a 14-bit infrared image and a precision casting image with defects. Quantitative experimental results indicate that the design method effectively highlights image texture details, demonstrating greater universality and adaptability for processing various types of greyscale image. Additionally, evaluation indicators reflecting human vision are improved. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Insight: Non-Destructive Testing & Condition Monitoring. 2026/04, Vol. 68, Issue 4, p267
- Document Type:Article
- Subject Area:Science
- Publication Date:2026
- ISSN:1354-2575
- DOI:10.1784/insi.2026.68.4.267
- Accession Number:193079581
- Copyright Statement:Copyright of Insight: Non-Destructive Testing & Condition Monitoring is the property of British Institute of Non-Destructive Testing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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