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Article type: Research Article
Authors: Zhao, Weia; b | Liu, Yia; b; * | Linghu, Xinyaoa; b | Zhang, Pengchenga; b | Yan, Hongxua; b | Ding, Xiaxua; b | Wang, Xianga; b | Gui, Zhiguoa; b | Chen, Yana; b
Affiliations: [a] School of Information and Communication Engineering, North University of China, Taiyuan, China | [b] State Key Laboratory of Dynamic Testing Technology, North University of China, Taiyuan, China
Correspondence: [*] Corresponding author: Liu Yi, Professor, School of Information and Communication Engineering, North University of China, No. 3, College Road, Taiyuan, Shanxi Province, 030051, China. Tel.: +13834200026; E-mail: liuyi@nuc.edu.cn.
Abstract: BACKGROUND:Recently, X-rays have been widely used to detect complex structural workpieces. Due to the uneven thickness of the workpiece and the high dynamic range of the X-ray image itself, the detailed internal structure of the workpiece cannot be clearly displayed. OBJECTIVE:To solve this problem, we propose an image enhancement algorithm based on a multi-scale local edge-preserving filter. METHODS:Firstly, the global brightness of the image is enhanced through logarithmic transformation. Then, to enhance the local contrast, we propose utilizing the gradient decay function based on fuzzy entropy to process the gradient and then incorporate the gradient into the energy function of the local edge-preserving filter (LEP) as a constraint term. Finally, multiple base layers and detail layers are obtained through filtering multi-scale decomposition. All detail layers are enhanced and fused using S-curve mapping to improve contrast further. RESULTS:This method is competitive in both quantitative indices and visual perception quality. CONCLUSIONS:The experimental results demonstrate that the proposed method significantly enhances various complex workpieces and is highly efficient.
Keywords: X-ray images, local edge-preserving filter, local fuzzy entropy, gradient domain compression, S-curve mapping
DOI: 10.3233/XST-240045
Journal: Journal of X-Ray Science and Technology, vol. 32, no. 4, pp. 1061-1077, 2024
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