【摘要】 针对时域高通滤波非均匀性校正算法中存在只对偏移响应系数进行校正、难以选取合适的时间常数以及滤波后图像细节不清晰等问题,本文通过分析时间常数对算法校正效果的影响,提出了一种改进的时域高通滤波非均匀性校正算法。首先采用离线采集的非均匀性噪声底图对红外焦平面阵列的原始输出图像进行预处理,去除部分固定模式噪声,保证了增益的均匀性;然后通过运动检测环节判断场景运动是否充分,根据运动程度自适应选取时间常数构造低通滤波器;最后运用高频提升滤波达到提升红外图像整体的亮度和增强目标细节的效果。对真实的红外视频图像实验表明,通过自适应选取时间常数有效地抑制了目标退化和伪像现象,且算法的收敛速度快,校正后图像细节清晰,有利于工程实时应用。更多还原

【Abstract】 The Temporal High-pass Filtering Nonuniformity Correction (THPF-NUC) algorithm has three major drawbacks, namely only correcting the offset coefficient, difficulty in choosing a proper time constant and unclear detail of corrected image. By analyzing the time constant’s effect on the correction quality, an improved THPF-NUC algorithm is proposed. Firstly, to guarantee the uniformity of the gain coefficient, the noise background image is subtracted from the output image of Infrared Focal Plane Arrays (IRFPA) as preprocessing. Then according to the motion degree obtained from the motion detection technique, adaptively adjust the time constant to design the low-pass filter. Lastly the high-boost filtering is adopted to improve the brightness of the whole IR image and enhance the details. The experiment on a real IR video shows that the proposed algorithm eliminates the ghosting artifact and the target fade-out effectively. And the corrected image is high quality with fast convergence rate, giving advantage to real-time engineering application.更多还原