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针对传统的基于场景的红外焦平面阵列非均匀性校正算法收敛速度慢和校正精度不高的缺点,提出了一种基于扩展全变分的红外焦平面阵列非均匀性校正方法。在分析全变分算法的图像去噪性能的基础上,针对运动的红外图像序列,扩展了全变分的应用范围。通过最小化非均匀校正后图像的全变分,利用最陡下降法,得到计算增益量校正因子和偏移量校正因子的迭代公式。针对校正图像存在的鬼影现象,设计了一种自适应阈值控制的鬼影消除方法。实验表明:相较于目前已有的方法,该方法有效地去除了原始红外图像的固定图案噪声,较大程度地保留了图像细节信息,提高了图像质量。
Aiming at the shortcomings of the traditional scene-based infrared focal plane array nonuniformity correction algorithm, such as slow convergence rate and low accuracy, a new method of nonuniformity correction of infrared focal plane array based on extended total variation is proposed. On the basis of analyzing the image denoising performance of the all-variation algorithm, the range of application of the total variation is expanded for the moving infrared image sequence. By minimizing the total variation of the non-uniformly corrected image and using the steepest descent method, an iterative formula for calculating the gain correction factor and the offset correction factor is obtained. Aiming at the ghosting phenomenon of the corrected image, an adaptive ghost elimination method of threshold control is designed. Experiments show that compared with the existing methods, this method effectively removes the fixed pattern noise of the original infrared image, preserves the image detail information to a great extent and improves the image quality.