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。     

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.     

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Savitzky-Golay加权拟合的红外图像非均匀性条带校正方法

针对红外成像探测器单元响应不一致等因素导致的图像非均匀性条带问题, 提出了基于直方图加权和Savitzky-Golay拟合的非均匀性条带校正方法。首先, 计算每列的归一化直方图函数并将其作为权值对图像进行加权运算;然后, 利用Savitzky-Golay滤波器对加权后的图像列均值和列方差进行拟合, 并将结果带入校正公式, 通过可调参数的迭代完成校正。实验结果表明:该方法能有效地去除非均匀性条带, 保留图像的光谱辐射信息和纹理细节, 各项评价指标均提高10%。     

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.     

干涉成像光谱仪CCD象元响应非均匀性校正研究

在阐述一般成像系统中CCD象元响应非均匀性校正的原理与算法的基础上,通过对星载可见光干涉成像光谱仪CCD象元响应非均匀性校正的相对辐射定标原理及所获定标数据的深入分析,研究出了一种适于对可见光及红外干涉成像光谱仪系统CCD象元响应非均匀性进行校正的方法,有效解决了干涉成像光谱仪系统探测器阵列非均匀性校正这一工程技术难题.     

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。     

基于反中值滤波的红外焦平面自适应非均匀性校正方法

分析了红外焦平面阵列非均匀性的噪声特性，提出了一种用反中值滤波为核心的红外焦平面自适应校正的方法。针对实际的图像进行了实验，实验证明该方法在校正效果、收敛速度、对静止目标保持能力及可硬件化等方面都有较好的表现。     

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。     

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.     

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.     

不同非均匀性校正温度的红外测温技术

为使制冷型中波红外热像仪在不同环境温度下经过非均匀性校正后保持较高的测温精度,研究了考虑非均匀性校正温度效应的中波红外热像仪标定模型。利用不同温度的面源黑体对热像仪进行非均匀性校正,然后对黑体目标进行测温实验,获得了不同校正温度下热像灰度与黑体辐射亮度之间的变化关系,建立了目标的测温数学计算模型,最后对测温结果进行误差分析。结果表明：在不同校正温度下,热像灰度相对非均匀校正辐亮度的漂移可做线性化处理,且与目标温度变化无关。在非均匀性较低的测温范围内热像仪的测温误差小于±0.22 ℃,极大减小了制冷型中波红外热像仪在不同校正温度下非均匀性校正后的测温误差。     

基于焦平面归一化响应特性的红外非均匀性校正

红外焦平面阵列的非均匀性噪音是制约红外成像质量的主要因素,非均匀性校正是红外焦平面器件应用的一个关键技术.本文提出了一种基于焦平面归一化响应特性且易于实现的非均匀性校正算法,并基于像元分布的卡方直方图提出一种新的图像非均匀性评估方法,即校正比例.该方法的校正输出考虑了每个像元的观测值与焦平面的响应信号的平均值,校正参量通过将像元的输出与其理想校正结果之间的偏差用焦平面响应的平均值建立联系而计算得到.提出的校正比例兼顾考虑了焦平面响应的时间与空间特性,比现有的图像非均匀性评估方法更能合理衡量焦平面的非均匀性程度.多种非均匀性校正的评价数据以及实验结果表明,该算法的校正效果优于两点校正法与原值拟合二阶校正法,并对于响应异常的像元具有较强的校正能力.此外其校正准确度高,所需参量少,易于实时处理,具有较强的实用价值.     

基于DSP的红外焦平面阵列非均匀性实时压缩校正研究

针对红外成像系统在图像处理中所涉及的数据量大,实时处理难于实现的特点,利用高速DSP硬件对红外焦平面阵列的非均匀性进行实时压缩校正.以两点校正为例,详细阐述了硬件压缩校正原理和实现步骤,并给出实验结果.实验表明:基于DSP的非均匀性实时压缩校正系统生成的图像比较清晰,校正过程简单,程序调试方便,能够有效地解决红外成像技术中实时性难题.     

Stripe noise removal for infrared image by minimizing difference between columns

This paper introduces a novel approach to eliminate stripe noise in infrared images. The differences between bias voltages in column readout circuit of uncooled infrared sensors result in strong stripe noise which changes slowly in time. The problem can be solved by estimating the bias of each column of infrared images and correcting infrared images with the estimated biases. The bias estimation is translated into an energy optimization problem in the paper. The optimization aims to minimize difference between neighboring columns of images. Our approach can be processed on a single image, or in a recursive way in order to significantly reduce the computation in one frame time. Our approach is compared to the state-of-the-art the stripe noise removal method using realistic infrared images, and the experimental results show the effectiveness and efficiencies of our proposed approach.     

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。     

Registration method for infrared images under conditions of fixed-pattern noise

This paper proposes a new registration method for infrared images under conditions of fixed-pattern noise (FPN). Conventional registration techniques are susceptible to FPN and it is therefore very desirable to have a registration algorithm that is tolerant to FPN. For this purpose, we utilize the difference of the cross-power spectrum of two discrete shifted images to suppress the noise power spectrum while the shifts information is well preserved. In particular, we show that the phase of the cross-power spectrum difference is a periodic two-dimensional binary stripe signal with the exact shifts determined to subpixel accuracy by the number of periods of the phase difference along each frequency axis. Robust estimates of shifts can be obtained by transforming its discontinuities to Hough domain. Experimental results show that the proposed method exhibits robust and accurate registration performance even for the noisy images that could not be handled by conventional registration algorithms. We have also incorporated this technique to a registration-based nonuniformity correction (NUC) framework, indicating that our registration technique is able to estimate motion parameters reliably, leading to satisfactory NUC result.