An enhanced non-uniformity correction algorithm for IRFPA based on neural network

Influenced by detector materials’ non-uniformity, growth and etching techniques, etc., every detector’s responsivity of infrared focal plane arrays (IRFPA) is different, which results in non-uniformity of IRFPA. And non-uniformity of IRFPA generates fixed pattern noises (FPN) that are superposed on infrared image. And it may degrade the infrared image quality, which greatly limits the application of IRFPA. Non-uniformity correction (NUC) is an important technique for IRFPA. The traditional non-uniformity correction algorithm based on neural network and its modified algorithms are analyzed in this paper. And a new improved non-uniformity correction algorithm based on neural network is proposed in this paper. In this algorithm, the desired image is estimated by using three successive images in an infrared sequence. And blurring effect caused by motion is avoided by applying implicit motion detection and edge detection. So the estimation image is closer to real image than the estimation image estimated by other algorithms, which results in fast convergence speed of correction parameters. A comparison is made to these algorithms in this paper. And experimental results show that the algorithm proposed in this paper can correct the non-uniformity of IRFPA effectively and it prevails over other algorithms based on neural network.     

Improvement in adaptive nonuniformity correction method with nonlinear model for infrared focal plane arrays

The scene adaptive nonuniformity correction (NUC) technique is commonly used to decrease the fixed pattern noise (FPN) in infrared focal plane arrays (IRFPA). However, the correction precision of existing scene adaptive NUC methods is reduced by the nonlinear response of IRFPA detectors seriously. In this paper, an improved scene adaptive NUC method that employs “S”-curve model to approximate the detector response is presented. The performance of the proposed method is tested with real infrared video sequence, and the experimental results validate that our method can promote the correction precision considerably.     

一种新的红外焦平面阵列非均匀性代数校正算法

 针对传统红外图像非均匀性代数校正算法收敛速度慢、运动估计精度不高的缺点,提出一种多尺度光流帧间运动估计的非均匀代数校正算法。通过时域低通滤波,采用多尺度光流估计下一帧图像,将所得图像对进行代数校正。该方法性能在自主研发的热像仪中得到验证,和传统的红外图像非均匀性代数校正算法相比,算法收敛速度从60帧提高到25帧,提高一倍左右,运动估计精度从校正后图像方差76.539减少到32.482。     

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.     

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.     

场景自适应的红外焦平面成像动态范围调整技术

针对红外焦平面对辐射强度较大的目标输出动态范围不足的问题,提出了一种场景自适应的红外焦平面成像动态范围调整技术。包括3个方面的内容：从图像中提取目标灰度特征,获取动态范围自适应依据;结合最小均方自适应滤波算法,对调整依据进行滤波预测后给出调节值;把灰度调节值转换成电平值,利用电平值设置红外焦平面偏置电压完成焦平面成像动态范围自适应。最后,对整体方案进行了实验验证。通过在红外焦平面成像系统中实验证明了基于场景成像动态范围自适应方法的可行性,并获得了很好的效果,成像质量有明显提高。     

场景自适应的红外焦平面成像动态范围调整技术

针对红外焦平面对辐射强度较大的目标输出动态范围不足的问题,提出了一种场景自适应的红外焦平面成像动态范围调整技术。包括3个方面的内容:从图像中提取目标灰度特征,获取动态范围自适应依据;结合最小均方自适应滤波算法,对调整依据进行滤波预测后给出调节值;把灰度调节值转换成电平值,利用电平值设置红外焦平面偏置电压完成焦平面成像动态范围自适应。最后,对整体方案进行了实验验证。通过在红外焦平面成像系统中实验证明了基于场景成像动态范围自适应方法的可行性,并获得了很好的效果,成像质量有明显提高。     

Guided filter and convolutional network based tracking for infrared dim moving target

The dim moving target usually submerges in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio. A tracking algorithm that integrates the Guided Image Filter (GIF) and the Convolutional neural network (CNN) into the particle filter framework is presented to cope with the uncertainty of dim targets. First, the initial target template is treated as a guidance to filter incoming templates depending on similarities between the guidance and candidate templates. The GIF algorithm utilizes the structure in the guidance and performs as an edge-preserving smoothing operator. Therefore, the guidance helps to preserve the detail of valuable templates and makes inaccurate ones blurry, alleviating the tracking deviation effectively. Besides, the two-layer CNN method is adopted to obtain a powerful appearance representation. Subsequently, a Bayesian classifier is trained with these discriminative yet strong features. Moreover, an adaptive learning factor is introduced to prevent the update of classifier’s parameters when a target undergoes sever background. At last, classifier responses of particles are utilized to generate particle importance weights and a re-sample procedure preserves samples according to the weight. In the predication stage, a 2-order transition model considers the target velocity to estimate current position. Experimental results demonstrate that the presented algorithm outperforms several relative algorithms in the accuracy.     

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.     

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。     

Non-uniformity correction of infrared focal plane array in point target surveillance systems

We discuss the influence of non-uniformity and non-uniformity correction on point target detection in infrared surveillance system, and propose a non-uniformity correction approach which is based on signal intensity and sensor characteristics. Theoretical models are used to derive the combined effect of background clutter, sensor random noise, target, non-uniformity and correction error on the signal-to-noise-and-clutter ratio. From our analysis, it can be noted that background clutter intensity is successively modulated by sensor non-uniformity and non-uniformity correction, while sensor random noise is modulated by the non-uniformity correction process only. Furthermore, background clutter and sensor random noise are the key factors that affect the performance of a surveillance system, when it is used to detect point targets. The method presented in this paper takes all of the above into account, moreover, it considers the difference between scanning and staring focal plane array. The experimental results demonstrate the effectiveness of the proposed method.     

基于BP神经网络的红外焦平面非均匀性校正技术

在传统BP神经网络非均匀性校正理论的基础上,结合红外焦平面阵列读出通道的时变特性,提出一种新的输出期望估计方法.该方法利用当前像素邻域和读出通道估计输出期望值.实验表明,算法能有效抑制焦平面固定图案噪音,提高场景目标的分辨能力,达到较好的视觉效果.     

无基底焦平面阵列的红外成像性能分析

利用提出的光学读出非制冷红外成像系统,先后制作了单元尺寸各不相同的单层膜无基底焦平面阵列(focal plane array,FPA),获得了室温物体的热图像.分析发现,当FPA的单元尺寸从200μm逐渐减小到60μm时,基于恒温基底模型的理论响应与实验结果的偏差逐渐增大.通过有限元分析方法,模拟分析了不同尺寸的微梁单元在无基底FPA中的热学行为,发现了当单元尺寸逐渐减小时恒温基底模型偏差逐渐增大的原因,即无基底FPA的支撑框架不满足恒温基底条件,受热辐射后支撑框架的温升从基底上抬高了单元的温升.论文还分 关键词： 光学读出 非制冷红外成像 焦平面阵列 无基底     

基于无基底焦平面阵列红外热像仪的理论模型分析

基于双材料微悬臂梁热变形原理的光学读出非制冷红外探测阵列经历了从有基底结构向无基底结构的发展过渡,无基底阵列的红外成像结果和有限元模型分析均表明无基底阵列不满足恒温基底条件.本文结合电学比拟的方法,提出了一种新的基于无基底焦平面阵列(focal plane Array,FPA)的热传递分析的理论模型.分析采用整体考虑的思路,避开了无基底FPA阵列各单元热传递互相影响所产生的复杂热分布分析,并考虑了框架对热量的吸收与传递.理论模型采用外边框与环境等温的边界条件,虽不及有限元方法对边界条件的处理灵活,但也已取 关键词： 光学读出 无基底 非制冷红外成像 焦平面阵列     

Design rule of indium bump in infrared focal plane array for longer cycling life

In light of the proposed equivalent method, a three-dimensional structural modeling of InSb infrared focal plane arrays (IRFPAs) is created, and the simulated strain distribution is identical to the deformation distribution on the top surface of InSb IRFPAs. After comparing the deformation features at different regions with the structural characteristics of IRFPAs, we infer that the flatness of InSb IRFPAs will be improved with a thinner indium bump array, and this inference is verified by subsequent simulation results. That is, when the diameter of indium bump is smaller than 20 μm, the simulated Z-components of strain on the whole top surface of InSb IRFPAs is uniform, and the deformation amplitude is small. When the diameter of indium bump is larger than 28 μm, the simulated Z-components of strain increases rapidly with the thicker indium bump, and the flatness of InSb IRFPAs is worsened rapidly. According to the changing trend of deformation amplitude with diameters of indium bump, and employing element pitches normalization method, a design rule of indium bump is proposed. That is, when the diameter of indium bump is shorter than 0.4 times the element pitch, the flatness of InSb IRFPAs is in an acceptable range. This design rule was supported by different IRFPAs with different formats delivered by several main research groups for achieving a longer cycling life.     

Thermal and mechanical characterizations of asubstrate-free focal plane array

We propose a substrate-free focal plane array (FPA) in this paper. The solid substrate is completely removed, and the microcantilevers extend from a supporting frame. Using finite element analysis, the thermal and mechanical characterizations of the substrate-free FPA are presented. Because of the large decrease in thermal conductance, the supporting frame is temperature dependent, which brings out a unique feature: the lower the thermal conductance of the supporting frame is, the higher the energy conversion efficiency in the substrate-free FPA will be. The results from the finite element analyses are consistent with our measurements: two types of substrate-free FPAs with pixel sizes of 200× 200 and 60× 60~μ m² are implemented in the proposed infrared detector. The noise equivalent temperature difference (NETD) values are experimentally measured to be 520 and 300~mK respectively. Further refinements are considered in various aspects, and the substrate-free FPA with a pixel size of 30× 30~μ m² has a potential of achieving an NETD value of 10~mK.     

制冷红外焦平面和热像仪的性能评价与验收

在对进口的制冷红外焦平面和红外热像仪进行性能评价与验收中,针对存在的问题,提出了一种新的基于制冷红外焦平面工作温度的简单易行的评价方法。通过测试制冷红外热像仪的两个关键指标,即制冷时间和探测器的工作温度,可以判断制冷红外热像仪是否合格,解决了在制冷红外热像仪验收过程中出现的问题。     

Bias-selectable mid-/long-wave dual band infrared focal plane array based on Type-II InAs/GaSb superlattice

In this paper, a mid-/long-wave dual-band detector which combined PπMN structure and unipolar barrier was developed based on type-II InAs/GaSb superlattice. A relevant 320 × 256 focal plane array (FPA) was fabricated. Unipolar barrier and PπMN structure in our dual band detector structure were used to suppress cross-talk and dark current, respectively. The two channels, with respective 50% cut-off wavelength at 4.5 μm and 10 μm were obtained. The peak quantum efficiency (QE) of mid wavelength infrared (MWIR) band and long wavelength infrared (LWIR) band are 53% at 3.2 μm under no bias voltage and 40% at 6.4 μm under bias voltage of −170 mV, respectively. And the dark current density under 0 and −170 mV of applied bias are 1.076 × 10⁻⁵ A/cm² and 2.16 × 10⁻⁴ A/cm². The specific detectivity of MWIR band and LWIR band are 2.15 × 10¹² cm·Hz^1/2/W at 3.2 μm and 2.31 × 10¹⁰ cm·Hz^1/2/W at 6.4 μm, respectively, at 77 K. The specific detectivity of LWIR band maintains above 10¹⁰ cm·Hz^1/2/W at the wavelength range from 4.3 μm to 10.2 μm under −170 mV. The cross-talk, selectivity parameter at 3.0 μm, about 0.14 was achieved under bias of −170 mV. Finally, the thermal images were taken by the fabricated FPA at 77 K.     

Design and results for a 345 GHz sis focal plane array using planar technology

We describe a focal plane array using antenna elements and SIS junctions photo-etched on a quartz substrate. The etched antenna is of a new strip-line type in which a two-dimensional corrugated horn is phase-corrected with a strip-line lens. Good beam efficiency is indicated by the measured antenna patterns. A DSB receiver temperature of 225 K was obtained with a number of imperfections still present.     

Theoretical analysis and experimental application of CDS CMOS integrated circuit for uncooled infrared focal plane arrays

In this paper, a typical correlated double sampling (CDS) complementary metal oxide semiconductor (CMOS) circuit for uncooled infrared focal plane array (IRFPA) is theoretically analyzed, the key factor of CDS CMOS integrated circuit is pointed out, and a new CDS integrated circuit which is high correlative for low-frequency noise is applied in an experimental readout chip for uncooled IRFPA. Theoretical analysis indicates that the sample transfer function of a noise source acted on by CDS processing is related to noise frequency and sampling time interval and the key factor of CDS circuit for reducing or eliminating noise in readout integrated circuit is the sampling time interval. The experimental readout chip with high noise-correlative CDS integrated circuit is fabricated to verify the theoretical analysis, which can be applied to uncooled IRFPAs.