小波变换的红外焦平面阵列非均匀性校正算法

红外焦平面阵列(IRFPA)的非均匀性是其应用中必须解决的技术难题之一。基于小波理论,提出了一种基于成像场景的红外焦平面非均匀性校正算法。该算法选择合适的小波函数对红外成像序列进行小波分解,而后对分解的信号计算出相应的统计量,从而得出红外焦平面非均匀性校正的偏置和增益校正系数,以此最终实现非均匀性校正。对真实红外序列图像的处理效果验证了该算法可较好地实现非均匀性校正。此外该算法对慢变化量具有较好的自适应性,可较好地抑制一般基于场景统计的非均匀性校正算法中出现的"人工虚影"的现象。

Nonuniformity-Correction Algorithm for Infrared Focal Plane Arrays Based on Wavelet Transform

Nonuniformity of infrared focal plane arrays(IRFPA) is a key problem that must be solved in its applications.Based on the theory of wavelet transform,a scene-based nonuniformity-correction(NUC) technique for IRFPA is presented.In this algorithm,the infrared image sequence is decomposed by the discrete sequence wavelet transform with an appropriate wavelet function.Its corresponding statistics are calculated,and then coefficients of the offset and the gain for IRFPA NUC are achieved ultimately.The algorithm achieves good nonuniformity-correction capability,which is validated by experiments of real infrared imaging procedure.And the algorithm can auto-adapt to the slow-change parameters that affect the NUC and can restrain the "artificial ghost" in some degree that appears in other scene-base NUC methods.