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A new destriping method combining moment matching and interpolation in infrared images

机译:一种结合矩匹配和插值的红外图像去条纹新方法

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Stripe noise is very common in uncooled infrared imaging systems and often severely degrades the image quality. Based on the analysis of existing methods, a new destriping method combining moment matching and interpolation was proposed. The method mainly consisted of three steps: Firstly, moment matching was used to eliminate most stripes. Then an adaptive algorithm was used to classify the left stripes into three types: one-pixel-width stripes, two-pixel-width stripes and local stripes. Finally, these left stripes were identified and removed with weighted multi-neighborhood interpolation. The algorithm was tested with IR images heavily polluted by stripe noises, and the result indicated that it could efficiently remove stripe noise and enhance the image quality significantly better than the single method discussed in literature.
机译:条纹噪声在未冷却的红外成像系统中非常常见,通常会严重降低图像质量。在对现有方法进行分析的基础上,提出了一种将矩匹配与插值相结合的去斑方法。该方法主要包括三个步骤:首先,使用矩量匹配来消除大多数条纹。然后采用自适应算法将左条纹分为三类:一像素宽的条纹,两像素宽的条纹和局部条纹。最后,通过加权多邻域插值法识别并去除了这些左条纹。该算法在条带噪声严重污染的红外图像上进行了测试,结果表明,与文献中讨论的单一方法相比,该算法可以有效地去除条带噪声并提高图像质量。

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