Stripe nonuniformity correction algorithm based on steering kernel fitting for single infrared images
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摘要: 针对红外线列和非制冷型焦平面成像系统存在列向条纹非均匀性的现象，提出了一种基于转向核的单帧条纹非均匀性校正新算法。首先，根据图像边缘的梯度特性确定转向核邻域主方向和大小，然后将每列像素的转向核估计值作为该列像素的期望值，以列向条纹非均匀性作为约束进行最小二乘拟合，计算得到每列像元的校正参数，并以一定概率接受最小二乘拟合的结果。当误差函数满足事先设定阈值时，单帧图像的非均匀性校正完成。实验结果表明，该算法具有稳定的收敛性，与同类算法相比能够更有效抑制条纹非均匀性，并且能够保留更多的图像边缘信息。Abstract: In order to correct the stripe nonuniformity for infrared images captured by infrared linear arrays and uncooled staring infrared focal plane arrays, a novel stripe nonuniformity correction algorithm based on steering kernel for single infrared image was proposed. Firstly, the principal directions and window sizes of steering kernels were determined by the gradient characteristics of infrared images. Then, the estimations of each column pixel were treated as expectations in least square fitting, which was in the constraint of vertical stripe models. The correction parameters in the iteration were obtained, and the image corrected was accepted with a certain probability. The iteration of nonuniformity correction should not be ended until the error function is below the threshold preset. Experimental results indicate that the proposed algorithm has stable and fast convergence. Compared with other three algorithms, the proposed algorithm has the advantage of reducing the stripe nonuniformity and preserving much more edge information.
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Key words:
- stripe nonuniformity /
- single infrared image /
- least square fitting /
- steering kernel
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