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Non-uniformity Correction Algorithm Based onPolynomial Fit Estimation

机译:基于多项式拟合估计的非均匀性校正算法

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Because of many advantages such as all-weather work, passive imaging, high sensitivity, high frame frequency and simple structure, etc., IRFPA (infrared focal plane array) sensors have become popular in civil and military applications. However, images obtained by IRFPA suffer from a common problem called FPN (fixed pattern noise), which severely degrades image quality and limits the infrared imaging applications, and they can hardly be used without non-uniformity correction (NUC) on IR image. Therefore, it is urged to perform the NUC processing. As we all know, the algorithms of non-uniformity correction can be classified into two main categories, the calibration-based algorithm and the scene-based algorithm. But each kind of algorithm has its disadvantages, in order to make up for the limitations, a novel non-uniformity correction algorithm based on polynomial fit estimation and a modified factor is proposed, which combines the advantages of the two algorithms. Experimental results demonstrate that the proposed NUC algorithm has a good NUC effect with a lower non-uniformity ratio.
机译:由于全天候工作,被动成像,高灵敏度,高帧频和结构简单等诸多优点,IRFPA(红外焦平面阵列)传感器已在民用和军事应用中流行。然而,通过IRPFA获得的图像遭受称为FPN(固定图案噪声)的普遍问题,这严重降低了图像质量并限制了红外成像应用,并且如果不对红外图像进行不均匀校正(NUC),则很难使用它们。因此,敦促执行NUC处理。众所周知,非均匀性校正算法可以分为两大类:基于校准的算法和基于场景的算法。但是每种算法都有其缺点,为了弥补这种局限性,提出了一种基于多项式拟合估计和修正因子的非均匀性校正算法,结合了两种算法的优点。实验结果表明,所提出的NUC算法具有良好的NUC效果,具有较低的不均匀率。

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