一种基于恒定统计的红外图像非均匀性校正算法  

A non-uniformity correction algorithm of infrared image sequences based on constant-statistics

作　　者：孟思岐 任侃[1] 路东明[1] 顾国华[1] 陈钱[1] Meng Siqi Ren Kan Lu Dongming Gu Guohua Chen Qian(School of Electronic and Optical Engineering,Nanjing University of Science and Technology, Nanjing 210094, China)

机构地区：[1]南京理工大学电子工程与光电技术学院,江苏南京210094

出　　处：《应用光学》2017年第2期304-308,共5页Journal of Applied Optics

基　　金：江苏省自然科学基金(BK20130769)

摘　　要：对红外焦平面阵列成像系统而言,基于场景的非均匀校正技术是处理固定图案噪声的关键技术。现有的非均匀校正算法主要被收敛速度和鬼像问题所限制。提出一种新的基于恒定统计算法的自适应场景非均匀校正技术。利用红外图像序列的时域统计信息结合提出的α修正均值滤波来估计探测器的参数,通过减少样本的渐进方差估计,完成成像系统的非均匀性校正。通过模拟和真实的非均匀性图像对算法的性能进行评价。实验结果表明,在继承恒定统计算法快速收敛的同时,图像峰值信噪比较恒定校正法及常系数α校正算法分别有44.5%和32.9%的提升,图像鬼像问题有明显改善。For infrared focal-plane array imaging system, scene-based non-uniformity correction is key technique to deal with fixed pattern noise. Existing algorithms are mainly restricted by convergence speed and ghosting artifacts. In this paper, a novel adaptive scene-based non-uniformity correction technique is presented, which is based on constant-statistics method （CS）. Utilizing temporal statistics of infrared image sequences, the proposed method applies an alpha-trimmed mean filter to estimate detector parameters and minimize sample asymptotic variance estimate. Performance of proposed technique is evaluated by simulation and real non-uniformity image. Experimental results show the proposed method inherits characteristics of fast convergence of CS method and increases peak signal to noise ratio by 44.5% and 32.9% respectively, and image ghost problem is improved obviously.

关 键 词：红外焦平面阵列 非均匀性校正 恒定统计 修正均值滤波 

分 类 号：TN216[电子电信—物理电子学]