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Fixed Pattern Noise Pixel-wise Linear Correction for Crime Scene Imaging CMOS Sensor

机译:用于犯罪现场成像CMOS传感器的固定模式噪声逐像素线性校正

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Filtered multispectral imaging technique might be a potential method for crime scene documentation and evidence detection due to its abundant spectral information as well as non-contact and non-destructive nature. Low-cost and portable multispectral crime scene imaging device would be highly useful and efficient. The second generation crime scene imaging system uses CMOS imaging sensor to capture spatial scene and bandpass Interference Filters (IFs) to capture spectral information. Unfortunately CMOS sensors suffer from severe spatial non-uniformity compared to CCD sensors and the major cause is Fixed Pattern Noise (FPN). IFs suffer from "blue shift" effect and introduce spatial-spectral correlated errors. Therefore, Fixed Pattern Noise (FPN) correction is critical to enhance crime scene image quality and is also helpful for spatial-spectral noise de-correlation. In this paper, a pixel-wise linear radiance to Digital Count (DC) conversion model is constructed for crime scene imaging CMOS sensor. Pixel-wise conversion gain G_(i,j) and Dark Signal Non-Uniformity (DSNU) Z_(i,j) are calculated. Also, conversion gain is divided into four components: FPN row component, FPN column component, defects component and effective photo response signal component. Conversion gain is then corrected to average FPN column and row components and defects component so that the sensor conversion gain is uniform. Based on corrected conversion gain and estimated image incident radiance from the reverse of pixel-wise linear radiance to DC model, corrected image spatial uniformity can be enhanced to 7 times as raw image, and the bigger the image DC value within its dynamic range, the better the enhancement.
机译:滤波多光谱成像技术由于其丰富的光谱信息以及非接触和非破坏性的特性,可能是犯罪现场记录和证据检测的潜在方法。低成本且便携式的多光谱犯罪现场成像设备将是非常有用和高效的。第二代犯罪现场成像系统使用CMOS成像传感器捕获空间现场,并使用带通干扰滤波器(IF)捕获光谱信息。不幸的是,与CCD传感器相比,CMOS传感器存在严重的空间不均匀性,主要原因是固定模式噪声(FPN)。 IF受“蓝移”影响,并引入空间光谱相关的误差。因此,固定模式噪声(FPN)校正对于提高犯罪现场图像质量至关重要,并且对于空间光谱噪声的去相关也很有帮助。本文为犯罪现场成像CMOS传感器构建了像素级线性辐射度到数字计数(DC)转换模型。计算逐像素转换增益G_(i,j)和暗信号非均匀性(DSNU)Z_(i,j)。此外,转换增益分为四个分量:FPN行分量,FPN列分量,缺陷分量和有效光响应信号分量。然后将转换增益校正为平均FPN列和行分量以及缺陷分量,以使传感器转换增益均匀。根据校正后的转换增益和从像素级线性辐射度到DC模型的逆向估计的图像入射辐射率,可以将校正后的图像空间均匀性提高到原始图像的7倍,并且图像DC值在其动态范围内越大,则更好的增强。

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