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作 者:方琳琳 张华[1,2] 邓豪[1,2] 王海 王姮[1,2] Fang Linlin;Zhang Hua;Deng Hao;Wang Hai;Wang Heng(School of Information Engineering,Southwest University of Science&Technology,Mianyang Sichuan 621010,China;Robot Technology Used for Special Environment Key Laboratory of Sichuan Province,Southwest University of Science&Technology,Mianyang Sichuan 621010,China)
机构地区:[1]西南科技大学.信息工程学院,四川绵阳621010 [2]西南科技大学特殊环境机器人技术四川省重点实验室,四川绵阳621010
出 处:《计算机应用研究》2022年第6期1886-1890,共5页Application Research of Computers
基 金:国家“十三五”核能开发科研资助项目(20161295);四川省科技计划资助项目(2021YFG0376)。
摘 要:针对Co60辐射环境中γ光子穿透CMOS图像传感器时致使场景图像存在斑块噪声的问题,提出了一种基于离群特征的γ辐射图像去噪方法。首先在序列图像中逐点获取对应的像素序列,并将该像素序列进行光照归一化以消除图像帧之间光照差异影响;然后在光照归一化后像素序列中利用噪声像素值的离群特性判断当前像素点是否为噪点;最后利用序列中各点的一、二阶离群特征筛选有效像素序列,并将其均值进行逆光照归一化以作为噪点修复的像素值。所提方法与多种典型去噪方法分别在高剂量率区和低剂量率区的真实γ辐射图像上进行了对比实验,该方法均取得了最佳去噪效果。In the Co60 radiation environment,gamma photons will cause speckle noise in the scene images when they penetrate the CMOS image sensor.So this paper proposed a denoising method for gamma radiation image,which was based on the outlier features of noise.This method firstly obtained a set of corresponding pixels in the sequence of images,and normalized the illumination of obtained pixels to eliminate the influence of the brightness difference among images.Then,it used the outlier features of the normalized pixels to detect the noise.Finally,it applied the first-order filtering and second-order filtering me-thod to select non-noise pixels,and the noise-repaired pixel was the mean of non-noise pixel.It compared proposed method with various typical denoising algorithms on real gamma radiation images which captured in high-dose and low-dose scenes respectively,and it achieves best denoising effect according to the experimental results.
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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