王俊霖, 桂海峰, 李兴隆, 刘阳, 吴建华. 基于中值滤波改进的辐射图像降噪算法[J]. 同位素, 2024, 37(4): 363-371. DOI: 10.7538/tws.2024.youxian.013
引用本文: 王俊霖, 桂海峰, 李兴隆, 刘阳, 吴建华. 基于中值滤波改进的辐射图像降噪算法[J]. 同位素, 2024, 37(4): 363-371. DOI: 10.7538/tws.2024.youxian.013
WANG Junlin, GUI Haifeng, LI Xinglong, LIU Yang, WU Jianhua. Improved Radiation Image Denoising Algorithm Based on Median Filtering[J]. Journal of Isotopes, 2024, 37(4): 363-371. DOI: 10.7538/tws.2024.youxian.013
Citation: WANG Junlin, GUI Haifeng, LI Xinglong, LIU Yang, WU Jianhua. Improved Radiation Image Denoising Algorithm Based on Median Filtering[J]. Journal of Isotopes, 2024, 37(4): 363-371. DOI: 10.7538/tws.2024.youxian.013

基于中值滤波改进的辐射图像降噪算法

Improved Radiation Image Denoising Algorithm Based on Median Filtering

  • 摘要: 为了解决核废物处置热室等辐照场中图像的降噪问题,本研究基于中值滤波,针对辐射噪点对算法进行相应改进,提出适用于强辐照场下图像降噪的算法。算法流程为噪点识别、噪点处理、细节保护。噪点识别从视觉观感出发,将像素值高出其周围并达到一定数值的标记为可疑点,并根据辐射噪点设定最大面积阈值,将大于面积阈值的区域排除;噪点处理基于中值滤波,自适应调整滤波窗口的大小;通过图像融合进行细节保护。通过与其他降噪算法进行比较可见,本算法对于辐射噪点的识别准确,降噪效果明显,并且最大程度地保护了画面的细节。本算法对于不同剂量率条件的辐射环境下具有较好的鲁棒性,在100 Gy/h的强辐照场下仍具有较好的去噪效果,可为核废物处置的智能化应用提供技术支持。

     

    Abstract: In order to solve the problem of image denoising in irradiation fields such as nuclear waste disposal hot cells, this study made corresponding improvements to the algorithm based on the idea of median filtering for radiation noise points, and finally proposed an algorithm suitable for image denoising in strong irradiation fields. The algorithm process is divided into three steps: noise recognition, noise processing and detail protection. Noise recognition starts from visual perception. If the pixel value is higher than its surrounding value and reaches the set threshold, it is marked as suspicious. By setting the maximum area threshold of radiation noise, the area larger than the threshold is excluded. The idea of median filtering is used to deal with noise, and the size of filtering window is adjusted adaptively. The protection of detail borrows from the idea of image fusion. Compared with other noise reduction algorithms, the results show that the proposed algorithm is accurate in the identification of radiated noise points, has obvious noise reduction effect, and protects the details of the picture to the greatest extent. The algorithm demonstrates good robustness under radiation environments with different dose rates, and still achieves effective denoising even under a strong irradiation field of 100 Gy/h. This can provide technical support for intelligent applications in nuclear waste disposal.

     

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