基于梯度场景的非均匀校正方法

长波红外探测器经常被用于机载红外预警系统中,常受严重的非均匀性噪声干扰。为了校正探测器的非均匀性,补偿辐射响应非线性,提出了一种基于梯度场景的非均匀性校正方法。给出了探测器辐射响应非均匀性的观测模型;以标准黑体和梯度场景作为参考源,在理论上推导出校正系数表达式;利用原理样机进行了外场实验,并探测民航客机目标。实验结果表明:与基于黑体的两点校正方法相比,利用本文方法进行非均匀性校正后的图像,局部标准差峰值由8.57降低到2.39;对于相距50.64km的空中客车A319型客机,目标的信杂比由4.87提高到11.22。本文算法可以有效降低图像局部标准差,适用于机载红外预警系统。     

基于相邻像素统计一致性的非均匀性校正方法

为了校正长波红外探测器辐射响应非均匀性,提出了一种基于相邻像素统计一致性的非均匀性校正方法.首先,对探测器辐射响应非均匀性建模;然后,利用均值算子估计相邻像素之间的比值,并递推求解校正系数;最后,搭建了原理样机对多种不同场景成像.实验结果表明:与基于黑体的标定方法相比,利用本文方法校正后的图像粗糙度由1.27×10~(-2)降低至1.13×10~(-2),局部标准差峰值由10.5降低至3.5,可以有效降低红外探测器非均匀性噪声.     

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.     

一种基于恒定统计的红外图像非均匀性校正算法

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。     

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.     

基于时域矩匹配的红外图像自适应非均匀性校正EI北大核心CSCD

非制冷红外焦平面阵列的响应非均匀性通常表现出与条带噪声相类似的特性。基于场景的校正算法是提高图像质量,补偿响应特性漂移的有效措施。在深入研究矩匹配理论的基础之上,提出了一种新的时域矩匹配非均匀性校正方法。利用相邻帧矩匹配后的图像对场景的变化列进行估计,并在时间域对校正参数进行自适应更新。利用真实的红外图像序列验证了该算法在收敛速度和去鬼影方面的优越性和有效性。     

基于干扰对消的红外焦平面非均匀性校正算法

红外焦平面器件的非均匀性产生机理复杂,难以准确拟合探测元响应曲线。提出了一种基于相关干扰抵消的非均匀性校正算法,以预先采集到的一帧黑体面源图像做为自适应干扰对消器的参考输入图像,自适应滤波器由参考输入图像迭代计算出待校正红外图像的空间噪声的最佳估计,实现从空间噪声中提取真实图像信号。自适应滤波算法采用变步长最小均方误差算法,减少了算法的运算量,提高了算法的收敛速度。理论分析以及针对实际红外图像的仿真结果表明,提出的算法校正效果好,收敛速度快,更易于工程实现。     

改进的基于积分时间定标的红外焦平面阵列非均匀性校正算法(英文)

红外焦平面阵列各探测元响应的非均匀性降低了图像的质量和温度分辨率,定标类和场景类校正算法为解决该问题提供了可行的途径.传统的基于黑体定标的校正算法由于其简单有效而被广泛使用,但是其缺点在于依赖黑体及其相关控温装置.本文提出了一种改进的基于积分时间定标的两级校正算法.在保持入射辐射不变的情况下,首先通过改变积分时间得到系列响应数据,然后利用最小二乘法估计出两点校正所需的初始校正系数,并对不同积分时间下的响应数据进行初校正,最后估计出一点校正系数.实验结果证明该方法具有计算量小、校正准确度高的优点,可取得优良的校正效果,并易于在硬件平台中实现.     

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.     

A two-frame approach for scene-based nonuniformity correction in array sensors

This paper introduces a new scene-based technique to correct the fixed-pattern noise (FPN) in array sensors. This method registers a pair of image frames exhibiting small relative scene translation and then the noise pattern can be reconstructed using the constrained least-squares estimation. The key advantage of this technique is that the accurate estimates of the bias nonuniformity can be obtained with only two images, without imposing any assumptions on the structure of the FPN. Besides, the method works on almost static scene, and therefore does not require larger scale global motion and statistical assumptions on the scene irradiance. We test our method on synthetically generated FPN as well as with real infrared data, and experimental results demonstrate the significant reduction in FPN, validating the effectiveness of our approach. Finally, we validate the feasibility and validity of using the proposed method as a first step fostering the success of more sophisticated registration-based time-evolving correction algorithms.     

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.     

自适应地空背景红外图像降噪增强方法

针对地空背景红外图像对比度低,噪声干扰大的特点,提出一种自适应的地空背景红外图像的增强方法。通过基于场景的非均匀校正去掉大部分固定图案噪声,对降噪后的图像进行多宽度窗口联合的局部对比度增强。此算法只需代数运算,原理简单,效果显著,尤其适用于地空背景,海空背景或太空背景的红外图像目标探测与识别。此算法能够自适应地补偿红外图像固定背景噪声的漂移,使低对比度图像的各级细节得到增强,而且能够在压制背景噪声的同时使隐藏在暗处的人眼不可识别的细节清晰自然的显现出来。     

基于特征结构相似度的遥感影像融合质量评价指标

在分析现有影像融合评价指标的基础上,根据人眼视觉特性,提出一种基于特征结构相似度的遥感影像融合评价指标.首先从原始影像和融合影像中提取空间特征和光谱特征,然后综合计算空间特征和光谱特征的结构相似度作为评价指标,达到评价影像质量的目的.通过对多种传感器获取的遥感影像进行融合实验,结果表明该客观评价方法与主观评价结果一致,...     

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.     

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.     

基于黑体标定的红外图像非均匀性校正系统设计

为提高某中波红外探测器的图像质量,设计了基于FPGA的红外图像实时处理系统,系统能够完成实时的非均匀性校正与盲元补偿处理。介绍了目前常用的非均匀性校正、盲元识别和补偿算法,并结合实际工程需求采用多点法进行非均匀性校正以及8点平均法进行盲元补偿。在仿真实验成功的基础上,基于FPGA平台构建了硬件平台。系统可以实现系数自定义更新,可以手动或自动完成非均匀性较正系数计算,以及实现盲元列表的自动更新操作。利用某国产中波红外探测器对处理系统进行了测试试验,实验结果表明:校正后图像非均匀性0.3%,盲元率0.001%。系统工作稳定、可靠,图像处理满足实时性和精度要求。