脉冲颗粒噪声估计法估算CMOS图像传感器辐照强度  

Pulse Particle Noise Estimation Method Based CMOS Image Sensor Radiation Intensity Estimation

作　　者：林奎成 赵伟[1] 吴柳青 LIN Kui-cheng;ZHAO Wei;WU Liu-qing(Institute of Materials,China Academy of Engineering Physics,Mianyang Sichuan 621900,China)

机构地区：[1]中国工程物理研究院材料研究所,四川绵阳621900

出　　处：《核电子学与探测技术》2021年第4期636-640,共5页Nuclear Electronics & Detection Technology

基　　金：国家自然科学基金(61601423)资助。

摘　　要：提出了一种基于自适应阈值分割和形态学灰度重建的图像脉冲颗粒噪声估计方法,用于CMOS图像传感器辐照噪声强度估计。分析了可由图像脉冲颗粒噪声估计辐照强度的依据;利用自适应國值估计方式,结合形态学膨胀腐蚀等操作,实现辐照图像中的弱光照区域分制;采用形态学灰度重建方法,检测弱光照区域的脉冲颗粒噪声分布,统计脉冲颗粒噪声的数量及面积。实验表明:该方法在降低图像边缘信息干扰方面优于高斯拉普拉斯算子方法,检测结果稳定性优于固定阈值二值化方法。An image impulse particle noise estimation method based on adaptive threshold segmentation and morphological gray reconstruction is proposed,which is used to estimate the radiation noise intensity of CMOS image sensor.The reason for taking advantage of pulse noise to estimate radiation intensity is analyzed.The poor light intensity area of image is divided by using the proposed adaptive segmentation method and morphological erosion and dilation.Morphological grayscale reconstruction is utilized to detect pulse noises in the poor light intensity area of image,then the quantity and area of pulse noises are calculated to represent the radiation intensity estimation result.The experimental results show that the proposed method has stronger anti-jamming capability of image edge information than Gauss Laplace operator and better effectiveness for pulse noises estimation than binaryzation method of fixed threshold.

关 键 词：CMOS图像传感器 形态学灰度重建 自适应分割 辐照强度 

分 类 号：TL816[核科学技术—核技术及应用]