Acta Optica Sinica, Volume. 40, Issue 18, 1834001(2020)

Enhancement Algorithm of Variable Energy X-Ray Fusion Images

Bin Liu, Pengxiang Zhao, Xia Zhao*, and Lichao Zhang
Author Affiliations
  • School of Information and Communication Engineering, North University of China, Taiyuan, Shanxi 030051, China
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    Variable energy X-ray imaging technology is an important method to realize the internal information detection of large thickness ratio targets. This method can use the gradually changing tube voltage to obtain the trans-illumination sub-graphs of different thickness regions in the workpiece, and then the high dynamic range digital image, which can completely represent the structural information of the workpiece, is realized by fusion. However, due to the limited dynamic range of the display device, the details in the fused high dynamic range X-ray image cannot be displayed effectively. In view of the above problem, we use the characteristic that one X-ray image mainly shows the information of a mutation structure and propose the algorithm based on nonlinear enhancement of image gradients. This algorithm uses the gray-scale change information in the enhanced image to achieve image enhancement and meanwhile is combined with the multi-resolution characteristics of the image to realize the enhancement and fusion of gradient images with different resolution levels, and thus the retention and enhancement of structural information with different degrees of change are realized. Finally, the experiment is designed to image a large thickness ratio target by variable energy X-ray and to enhance the fused high dynamic range image. The results show that this method can be used to effectively enhance the structural information of a high dynamic range image.

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    Bin Liu, Pengxiang Zhao, Xia Zhao, Lichao Zhang. Enhancement Algorithm of Variable Energy X-Ray Fusion Images[J]. Acta Optica Sinica, 2020, 40(18): 1834001

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    Paper Information

    Category: X-Ray Optics

    Received: Apr. 8, 2020

    Accepted: Jun. 11, 2020

    Published Online: Aug. 28, 2020

    The Author Email: Zhao Xia (zhaoxia0316@nuc.edu.cn)

    DOI:10.3788/AOS202040.1834001

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