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A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor

机译:基于灰度补偿的TDI CMOS图像传感器固定模式噪声校正方法

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摘要

In order to eliminate the fixed-pattern noise (FPN) in the output image of time-delay-integration CMOS image sensor (TDI-CIS), a FPN correction method based on gray value compensation is proposed. One hundred images are first captured under uniform illumination. Then, row FPN (RFPN) and column FPN (CFPN) are estimated based on the row-mean vector and column-mean vector of all collected images, respectively. Finally, RFPN are corrected by adding the estimated RFPN gray value to the original gray values of pixels in the corresponding row, and CFPN are corrected by subtracting the estimated CFPN gray value from the original gray values of pixels in the corresponding column. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination with the proposed method, the standard-deviation of row-mean vector decreases from 5.6798 to 0.4214 LSB, and the standard-deviation of column-mean vector decreases from 15.2080 to 13.4623 LSB. Both kinds of FPN in the real images captured by TDI-CIS are eliminated effectively with the proposed method.
机译:为了消除时滞积分CMOS图像传感器(TDI-CIS)输出图像中的固定模式噪声(FPN),提出了一种基于灰度补偿的FPN校正方法。首先在均匀照明下捕获一百个图像。然后,分别基于所有收集图像的行均值向量和列均值向量来估计行FPN(RFPN)和列FPN(CFPN)。最后,通过将估计的RFPN灰度值添加到对应行中的像素的原始灰度值来校正RFPN,并且通过从对应列的像素的原始灰度值中减去估计的CFPN灰度值来校正CFPN。基于128级TDI-CIS的实验结果表明,在用所提出的方法校正在均匀照明下捕获的图像中的FPN之后,行均值矢量的标准偏差从5.6798 LSB降低到0.4214 LSB,列均值向量的偏差从15.2080降低到13.4623 LSB。该方法有效地消除了TDI-CIS捕获的真实图像中的两种FPN。

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