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RGB-NIR imaging with exposure bracketing for joint denoising and deblurring of low-light color images

机译:带有包围曝光的RGB-NIR成像,用于对弱光彩色图像进行联合降噪和去模糊

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Color images taken in low light scenes are deteriorated with noise and motion blur. The simultaneous reduction of noise and motion blur from the low-light color images is difficult because the imposed noise hinders accurate motion blur kernel estimation. To overcome this problem, we build a novel imaging system using a single sensor that captures red, green, blue (RGB) and near-infrared (NIR) images. Our imaging system captures low-light scenes with exposure bracketing, which is a technique to acquire multiple images with different exposure times. It thus allows us to obtain the short- and long-exposure RGB/NIR images. Both the short- and long-exposure NIR images taken using an NIR flash unit can be captured with less noise; thus they enable estimation of motion blur kernel accurately. Based on this fact, we perform joint denoising and deblurring of the low-light color image with the estimated motion blur kernel. Our experiments using real raw data captured by our imaging system demonstrate the effectiveness of our method.
机译:在弱光场景下拍摄的彩色图像会因噪点和运动模糊而变差。很难同时降低低光彩色图像的噪声和运动模糊,因为强加的噪声会阻碍精确的运动模糊核估计。为了克服这个问题,我们使用单个传感器构建了一个新颖的成像系统,该传感器可以捕获红色,绿色,蓝色(RGB)和近红外(NIR)图像。我们的成像系统通过包围曝光来捕获微弱的场景,这是一种获取具有不同曝光时间的多张图像的技术。因此,它使我们可以获得短曝光和长曝光RGB / NIR图像。使用NIR闪光灯拍摄的短曝光和长曝光NIR图像都可以以较少的噪声捕获;因此,它们可以准确估计运动模糊内核。基于这一事实,我们使用估计的运动模糊核对弱光彩色图像执行联合降噪和去模糊处理。我们使用由成像系统捕获的真实原始数据进行的实验证明了我们方法的有效性。

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