基于稳态卡尔曼滤波的红外焦平面阵列非均匀校正算法

传统的卡尔曼滤波算法利用批处理实现非均匀校正,这样不仅会带来较大的计算量和存储量,而且更重要的是该方法不能实时处理.为此,提出了一种基于稳态卡尔曼滤波的红外焦平面阵列非均匀校正算法,它可以根据固定图案噪声的特点离线计算出滤波器的增益矩阵,并且非均匀校正过程也采用了逐帧迭代方式,因此大大降低了计算复杂度和存储占用量.详细阐述了该算法的基本原理,并用仿真数据和真实红外数据对算法性能进行验证,实验结果表明:本方法平均校正一帧图像所需CPU时间和内存占用量分别为1.7188 s和131.25 KB,完全可以满足实时处理的要求.     

基于自适应滤波的红外焦平面阵列非均匀性校正算法

 红外探测器响应漂移特性会降低红外焦平面阵列（IRFPA）非均匀性校正的精度。针对该问题提出了一种基于场景的IRFPA非均匀性校正算法。该算法利用所获得的序列成像场景信息,采用一种基于快速自适应滤波器的最优化递归估计方法来获得非均匀性校正参数,并利用当前的成像信息来更新校正参数,以此降低探测器响应漂移特性对非均匀性校正的影响。算法仿真实验显示,对非线性参数为26.12%的同一图像,使用该算法、两点校正算法和卡尔曼滤波校正算法校正1 h后,可分别将非线性参数降至1.856%,3.122%和1.893%,说明该算法可获得稳定而较好的非均匀性校正效果。     

A new adaptive nonuniformity correction algorithm for infrared line scanner based on neural networks

The striping pattern nonuniformity of the infrared line scanner (IRLS) severely limits the system performance. An adaptive nonuniformity correction (NUC) algorithm for IRLS using neural network is proposed.It uses a one-dimensional median filter to generate ideal output of network and can complete NUC by a single frame with a high correction level. Applications to both simulated and real infrared images show that the algorithm can obtain a satisfactory result with low complexity, no need of scene diversity or global motion between consecutive frames. It has the potential to realize real-time hardware-based applications.     

Three-step nonuniformity correction for a highly dynamic intensified charge-coupled device star sensor

A three-step nonuniformity correction algorithm based on the photoelectrical response models of intensified charge-coupled device (ICCD) for a highly dynamic ICCD star sensor is proposed in the current paper. The influence factors of nonuniformity correction precision are analyzed based on the photoelectrical imaging theory. The photoelectrical response models of ICCD are obtained using the experimental method, and the nonuniformity correction is implemented in three steps based on the photoelectrical response models. The nonuniformity correction results in constant-radiance images and sky images of the highly dynamic star sensor show that the proposed algorithm has satisfactory correction precision, and the accuracy of the highly dynamic star sensor can be enhanced effectively when sky images are processed using the three-step nonuniformity correction algorithm.     

基于场景的红外焦平面阵列非均匀性评价方法

针对红外遥感图像非均匀性的定量评价问题,研究了基于场景的红外焦平面阵列响应非均匀性的定量评价方法。利用真实红外遥感图像序列量值分布的特点,针对小序列图像提出了基于序列排序和小波变换的标准图像构建算法;结合非均匀性评价指标,提出了利用构建标准图像的响应非均匀性对红外图像的非均匀性进行定量估计;分别利用黑体定标实验和统计方法对标准图像构建算法进行了验证,同时进行了不同校正算法的剩余非均匀性评价实验。结果表明,128frame序列构建得到的标准图像的非均匀性分别比同温黑体图像小0.92%,比统计标准图像大0.59%。该方法可用于定量估计红外遥感图像的非均匀性。     

一种新的基于平稳小波变换的红外焦平面非均匀性校正技术

在分析固定图案噪音频率分布的基础上,提出了一种利用平稳小波进行非均匀性校正的方法.选择合适的小波函数对红外图像序列进行分解,从而估计出非均匀性校正的增益和偏置系数,最终实现红外焦平面阵列的非均匀性校正.利用小波的多分辨性质,提高了低频部分的频率分辨率,有效的抑制了一般基于场景统计校正算法中易于出现的“人工鬼影”现象.用真实的红外图像序列进行了处理,实验证明了算法的优越性.     

Efficient single image stripe nonuniformity correction method for infrared focal plane arrays

We present a novel, stripe nonuniformity correction algorithm for infrared focal plane arrays. This method relies on the separation of nonuniformity and true scene, and the nonuniformity correction parameter is obtained by traversing the error function of two adjacent columns?? pixels in local template window. Based on the succession of two adjacent columns?? correlation, the stripe nonuniformity correction can be achieved in a single frame. Experimental results, to illustrate the performance of the method, include the use of infrared image sequences with simulated nonuniformity and a diverse set of real IR imagery.     

基于特征分解的红外焦平面非均匀性校正算法

针对目前红外焦平面自适应场景校正算法工程应用的局限,提出了一种基于红外焦平面非均匀性特征分解的场景校正算法。分析了红外焦平面非性匀性构成因素,把其中的高频部分分解成盲点、斑块、行列非均匀性等,把缓慢变化的低频部分分解成梯度渐变非均匀性;分别对各类非均匀性采用不同的校正算法;合并校正结果,得到校正后的图像。实验结果表明,该算法校正精度高、收敛速度快、抑止目标退化能力强,适合工程应用。     

Nonuniformity correction algorithm based on adaptive filter for infrared focal plane arrays

Response nonuniformity is a key problem that influences the imaging performance of infrared focal plane arrays (IRFPA) imaging system. A parallel processing algorithm to adaptively estimate the nonuniformity correction (NUC) parameters for IRFPA is presented. In this algorithm, a bank of the adaptive filter is applied to adaptively estimate the NUC parameters for every detector in IRFPA. The infrared image sequences are input into the bank of adaptive filter. After certain times recursion calculations are executed frame-by-frame, then the optimal coefficients of the gain and the offset of detector in IRFPA are achieved. Then the NUC is fulfilled ultimately. The algorithm reduces the influence that the response drift with time imposed on NUC effectively, and achieves good NUC effect. It was validated by real experimental imaging procedures.     

Minimum mean square error method for stripe nonuniformity correction

Stripe nonuniformity is very typical in line infrared focal plane (IRFPA) and uncooled starring IRFPA. We develop the minimum mean square error (MMSE) method for stripe nonuniformity correction (NUC). The goal of the MMSE method is to determine the optimal NUC parameters for making the corrected image the closest to the ideal image. Moreover, this method can be achieved in one frame, making it more competitive than other scene-based NUC algorithms. We also demonstrate the calibration results of our algorithm using real and virtual infrared image sequences. The experiments verify the positive effect of our algorithm.     

基于变积分时间的红外焦平面非均匀性校正算法研究

针对两点温度定标算法在应用过程中曝露的问题,提出了基于变积分时间的红外焦平面非均匀性校正算法.该算法先对图像进行非线性压缩,转换为线性图像,再利用红外焦平面阵列探测元的响应特性与积分时间之间的关系,采用改变积分时间的方法拟合红外焦平面探测器的平均响应特性曲线,进行两点校正,然后对结果进行取指数操作,即得到原图非均匀校正后的图像.分别利用两点温度定标法和变积分法对航拍红外图像进行校正效果验证,同时进行了不同校正算法的非均匀性适应性评价实验.实验结果表明新算法计算量小,校正准确度高,反应速度快,并在一定程度上解决了大动态范围下响应非线性对校正性能的影响,具有很好的工程应用价值.     

基于帧间预测的红外焦平面阵列非均匀校正算法

提出了一种基于帧间预测的非均匀校正算法,它可以通过场景配准从当前已校正图像中估计出下一帧未校正图像的真值,然后将所得的场景估计与相应的噪音图像用于线性拟合,其拟合参量即可用来进行非均匀校正.该方法的主要优点在于抗噪音能力强,预测准确度高,且能够实时处理.详细阐述了算法的基本原理及其流程,并用真实红外数据对算法性能进行验证,取得了较好的效果.     

Scene based nonuniformity correction based on block ergodicity for infrared focal plane arrays

This paper puts forward a new scene based nonuniformity correction algorithm for IRFPA. This method adopts phase-correlation method for motion estimation and takes the sum of mean-square errors of the pixel brightness between several adjacent frames as the cost function when the brightness constancy assumption between two adjacent frames is satisfied. Nonuniformity correction parameters could be estimated by minimizing such cost function. In order to reduce calculation quantity, we can divide these images into several subblocks, and solve for the optimum solution of the cost function respectively in each subblock. From the analysis, it is shown that the optimum solution is of global uniqueness when all the elements in subblocks could satisfy the ergodicity condition. Then the estimated value of nonuniformity correction parameters could be deduced by minimizing the cost functions. The nonuniformity correction experiments for both infrared image sequence with simulated nonuniformity and infrared imagery with real nonuniformity show that the proposed algorithm could achieve a great correction effect by only analyzing a small number of frames.     

一种基于区域分割与跟踪的多视点视频校正算法

针对多视点图像系统中视点图像颜色不一致的问题,提出了基于区域分割与跟踪的多视点视频校正算法.采用3维高斯混合模型来描述颜色信息,利用期望-最大算法来精炼模型参量,并通过自适应聚类和概率平滑操作来得到精确的分割图像.这样建立起多视点图像分割区域间的局部映射关系,并利用这种局部映射关系对全局图像进行校正.最后利用视频跟踪技术实现对视频图像的校正.实验结果表明,该算法能消除颜色过饱和或颜色区域混淆的影响,且具有较好的校正效果.     

Improved interframe registration based nonuniformity correction for focal plane arrays

In this paper, an improved interframe registration based nonuniformity correction algorithm for focal plane arrays is proposed. The method simultaneously estimates detector parameters and carries out the nonuniformity correction by minimizing the mean square error between the two properly registered image frames. A new masked phase correlation algorithm is introduced to obtain reliable shift estimates in the presence of fixed pattern noise. The use of an outliers exclusion scheme, together with a variable step size strategy, could not only promote the correction precision considerably, but also eliminate ghosting artifacts effectively. The performance of the proposed algorithm is evaluated with clean infrared image sequences with simulated nonuniformity and real pattern noise. We also apply the method to a real-time imaging system to show how effective it is in reducing noise and the ghosting artifacts.     

一种基于场景的红外图像非均匀性校正算法

提出了一种基于场景的红外图像非均匀性校正算法。该算法结合了两点定标校正算法和基于场景的改进的恒定统计算法,将两点校正算法的校正系数作为恒定统计算法的系数初值,并引入阈值进行运动状态检测,对运动场景和非运动场景分别进行系数更新。实验表明,该算法可以实现对红外图像非均匀性的校正,对于本文实验中的视频图像,在100帧时算法收敛,其收敛时间优于其他传统基于场景的非均匀性校正算法,并一定程度上抑制了"鬼影"现象。     

基于自适应扩散模型的单帧红外条纹非均匀性校正算法

针对红外焦平面成像系统存在列向条纹非均匀性的现象,采用了一种基于自适应PM扩散模型的非均匀校正新算法。首先,综合利用图像梯度信息和局部灰度统计信息,自适应计算PM模型的扩散阈值;然后将每列像素的PM模型估计值作为该列像素的期望值;最后采用最陡下降法迭代计算得到每列像元的校正参数,并对结果进行循环校正以提高校正效果。实验结果表明:该算法可以保护图像边缘信息,与同类算法相比,能够更有效地抑制条纹非均匀性,并且能够防止图像产生鬼影。     

基于维纳滤波的红外焦平面阵列非均匀性校正算法

充分利用红外图像的空间相关性和时间相关性,提出了一种基于维纳（Wiener）滤波的红外焦平面阵列（IRFPA）非均匀性校正算法,实现对辐射信号的无偏估计,滤波器的参量通过时域一、二阶统计结合空域平均获得,同现有的典型校正算法相比,本文算法具有收敛速度快、校正准确度高的特点,理论分析以及针对实际红外图像的实验结果表明提出的算法更具优越性.     

基于三次样条插值的IRFPA非均匀性校正算法*

针对红外成像制导跟踪系统工程应用的实际要求,对红外焦平面阵列工作在大动态范围条件下的非均匀性校正算法进行了深入研究,依据函数插值原理,导出了三次样条插值非均匀性校正算法.用模拟的非均匀性图像和实际的红外图像对算法进行了校验.结果表明该算法具有动态范围大、校正准确度高的优点,可对红外焦平面阵列实现非均匀性和非线性双重校正效果.     

基于三次样条插值的IRFPA非均匀性校正算法

针对红外成像制导跟踪系统工程应用的实际要求,对红外焦平面阵列工作在大动态范围条件下的非均匀性校正算法进行了深入研究,依据函数插值原理,导出了三次样条插值非均匀性校正算法.用模拟的非均匀性图像和实际的红外图像对算法进行了校验.结果表明该算法具有动态范围大、校正准确度高的优点,可对红外焦平面阵列实现非均匀性和非线性双重校正效果.