【作者】 周波； 罗音； 陈宝国； 王明昌； 彭立； 梁琨；

【Author】 Bo Zhou;Yin Luo;Baoguo Chen;Mingchang Wang;Li Peng;Kun Liang;School of Electronic Information and Communications, Huazhong University of Science and Technology;Luoyang Opto-Electro Technology Center;

【机构】 华中科技大学电子信息与通信学院； 洛阳光电技术中心；

【摘要】 条纹非均匀性通常存在于红外图像中并影响视觉效果,因此消除条纹非均匀性对于提高图像质量是至关重要的。通常,条纹非均匀性校正的步骤是在非均匀校正(non-uniformity correction,NUC)预处理后进行的,这往往会破坏条纹非均匀性的数理统计特征,从而导致校正参数之间存在不同的偏差。在实施了初步的NUC后,同一列局部相邻的像素的条纹非均匀性差别较小且依然在空间上相关。因此,本文中提出了一个有着较高精度的校正模型,根据同一列相邻像素固有的空间相关性计算各像素的校正参数。实验结果表明本文提出的算法能有效去除不同场景的图像条纹非均匀性且在保持图像细节方面效果较好。此外,该算法具有很好的实时性。更多还原

【Abstract】 Stripe non-uniformity typically exists in infrared images and affects the visual effect; thus, eliminating stripe non-uniformity is essential to improve image quality. Typically, stripe non-uniformity correction is a step performed after preliminary non-uniformity correction(NUC) and can break the statistic characteristics of stripe nonuniformity and result in different deviations of the correction parameters. After applying early NUC, the diffe rences between the stripe non-uniformity of local adjacent pixels in the same column are small and still relevant in space. Thus, a correction model with higher accuracy is developed in the study. The proposed method calculates the correction parameters for each pixel based on the intrinsic spatial correlation between adjacent pixels in a column. The experimental results indicate that the proposed algorithm effectively eliminates stripe noise of images of different scenes and it also works well in terms of preserving details. Furthermore, the algorithm exhibits high real-time performance.更多还原