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.     

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.     

Fast iterative adaptive nonuniformity correction with gradient minimization for infrared focal plane arrays

A fast scene-based nonuniformity correction algorithm is proposed for fixed-pattern noise removal in infrared focal plane array imagery. Based on minimization of L0 gradient of the estimated irradiance, the correction function is optimized through correction parameters estimation via iterative optimization strategy. When applied to different real IR data, the proposed method provides enhanced results with good visual effect, making a good balance between nonuniformity correction and details preservation. Comparing with other excellent approaches, this algorithm can accurately estimate the irradiance rapidly with fewer ghosting artifacts.     

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。     

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.     

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.     

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。     

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.     

基于衬底温度和贝叶斯估计的红外非均匀性校正（英）

分析了红外焦平面阵列(IRFPA)基于定标的非均匀性校正法(NUC)和基于场景的NUC算法各自的优势和问题,在此基础上提出了联合非均匀性校正方法。根据上电时刻焦平面衬底的温度值,从FLASH中提取事先存储的对应温度区间的增益和偏置校正参数,初步消除探测器的非均匀性。通过分析初步校正后图像残余非均匀性噪声的特性,提出了一种自适应非均匀性校正算法NSCT,对经过NSCT分解后的子带图像,利用贝叶斯阈值逐点进行信号方差和噪声方差估计,计算出残余非均匀性噪声后并加以去除。实验结果表明,该算法能有效提高校正精度,并具有更强的环境适应性。     

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.     

X射线图像增强器像元响应不一致性的分析及校正

X射线图像增强器像元响应不一致性是评定图像质量的重要指标,它将影响设备的探测能力和分类级别,因而很有必要对不一致性的进行校正。通过对不一致性产生机理的理论分析,建立了图像增强器的每个像元通道光电响应的对数曲线模型。基于该模型,提出了一种改进的两点校正算法。该算法首先将非线性响应转化为线性响应,然后用基于最小二乘的多点校正算法对线性数据进行校正。校正前后的图像及标准差给出了对比,实验结果表明了该校正方法的有效性。     

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.     

Correction of aeroheating-induced intensity nonuniformity in infrared images

Aeroheating-induced intensity nonuniformity effects severely influence the effective performance of an infrared (IR) imaging system in high-speed flight. In this paper, we propose a new approach to the correction of intensity nonuniformity in IR images. The basic assumption is that the low-frequency intensity bias is additive and smoothly varying so that it can be modeled as a bivariate polynomial and estimated by using an isotropic total variation (TV) model. A half quadratic penalty method is applied to the isotropic form of TV discretization. And an alternating minimization algorithm is adopted for solving the optimization model. The experimental results of simulated and real aerothermal images show that the proposed correction method can effectively improve IR image quality.     

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.     

Nonuniformity correction of infrared images based on infrared radiation and working time of thermal imager

The spatial fixed-pattern noise (FPN) reduces the quality of the infrared image seriously, even makes infrared images inappropriate for some applications. In order to lower the FPN, some critical nonuniformity correction (NUC) algorithms such as NUC based on linear model, scene-based NUC and so on have been developed. But the algorithms have some drawbacks: restricted application in small dynamic range of objects temperature, low performance under the drift with the working time and complex calculations. In these cases, we develop a bivariate and quadratic model (bivariate is radiation and working time) of the FPA and the NUC technique based on the model. The proposed method is a true reflection of the infrared response and is a good solution for hardware implementation. It overcomes the drawbacks of the critical algorithm mentioned above. The last simulations and experiments show that the proposed algorithm exhibits a superior correction effect in both large objects temperature range and long working time of the thermal imager.     

Non-uniformity correction algorithm for IRFPA based on motion controllable micro-scanning and perimeter diaphragm strips

Non-uniformity correction is the key issue for the image quality improvement of infrared focal panel array (IRFPA) imaging. A non-uniformity correction (NUC) algorithm for IRFPA based on motion controllable micro-scanning platform and perimeter diaphragm strips is presented. We initially execute one-point calibration to the perimeter detectors, then based on controllable motion of adjacent frames, a special algebraic algorithm is proposed to transport the calibration of the perimeter detectors to those interior un-corrected ones. In this way, the bias parameter of the whole field of view (FOV) is calculated. The algorithm can be easily combined with sub-pixel imaging, thereby improving the quality of thermal imaging system (image spatial resolution and uniformity). All calculations are algebraic, with a low computation load. The algorithm can realize adaptive one point calibration without covering the central FOV rapidly. Experiments on simulated infrared data demonstrate that this algorithm requires only dozens of frames to obtain high quality corrections.     

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.     

函数拟合红外焦平面阵列非均匀性校正FPGA实现研究

结合红外焦平面阵列（Infrared Focal Plane Array,IRFPA）非均匀性校正的工程实际,设计了基于函数拟合的校正算法,采用大容量高速现场可编程门阵列（Field Programmable Gate Array,FPGA）器件,实现了该非均匀性校正系统,它能有效适应红外焦平面阵列器件响应特性的大动态范围和非线性,具有体积小、运算速度快和校正准确度高等优点.