用视频去闪烁算法修复红外图像列噪声，实时高效无伪影。
Efficient single image non-uniformity correction algorithm
- 将视频去闪烁法应用于图像列数据，实现单图去非均匀性。
- 每像素仅需两次操作，处理速度极快，支持实时应用。
- 无需标定板、无运动补偿，适合实际部署的静态场景。
本文提出一种新的方法来校正未制冷红外图像中的非均匀性（NU）问题。这类图像的主要缺陷是缺乏列（或行）随时间变化的交叉校准，导致强烈的列（或行）相关且随时间变化的噪声，可视为帧内列的1D闪烁现象。因此，经典视频去闪烁算法可被改编用于均衡图像列（或行）。所提方法对红外图像的列序列应用视频去闪烁算法，形成一种单图修正方法，适用于静态图像，无需图像配准、相机运动补偿或闭光圈传感器校准。该方法仅依赖一个相机相关参数，且与拍摄方向无关。在真实和模拟数据上，与最先进的总变差单图校正方法相比，该方法具有实时性能，每像素仅需两次操作，无需测试图案标定，且不产生“鬼影”伪影。
原文摘要 · Abstract (English)
This paper introduces a new way to correct the non-uniformity (NU) in uncooled infrared-type images. The main defect of these uncooled images is the lack of a column (resp. line) time-dependent cross-calibration, resulting in a strong column (resp. line) and time dependent noise. This problem can be considered as a 1D flicker of the columns inside each frame. Thus, classic movie deflickering algorithms can be adapted, to equalize the columns (resp. the lines). The proposed method therefore applies to the series formed by the columns of an infrared image a movie deflickering algorithm. The obtained single image method works on static images, and therefore requires no registration, no camera motion compensation, and no closed aperture sensor equalization. Thus, the method has only one camera dependent parameter, and is landscape independent. This simple method will be compared to a state of the art total variation single image correction on raw real and simulated images. The method is real time, requiring only two operations per pixel. It involves no test-pattern calibration and produces no "ghost artifacts".
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