红外焦平面阵列非均匀性非线性校正新方法

针对红外焦平面阵列非均匀性线性校正方法存在较大误差,而考虑非线性响应的校正算法又过于复杂,难于在实际工程中获得运用等难题,本丈提出一种易于硬件实时处理、校正精度较高的红外焦平面阵列非均匀性非线性校正新方法.在介绍非线性校正新方法原理的基础上,推导出其数学模型,并给出实验结果.实验结果表明该校正方法的校正精度达到1.2%,校正过程中需要存储的参数仅为4个/1象素,易于硬件实现实时校正.     

利用FPGA实现红外焦平面阵列实时非均匀性校正

实时非均匀性校正是红外成像的一项关键技术。根据红外焦平面阵列探测元光谱响应的特点和基于参照源的两点温标非均匀性校正理论，提出一种利用FPGA硬件实现红外焦平面阵列实时非均匀性两点校正的新方法。该方法动态范围大、处理速度快，适用于红外成像系统实时图像处理场合。仿真和实验结果证明是可行的。     

基于维纳滤波的红外焦平面非均匀性校正算法

针对焦平面阵列上各探测单元光电响应的非均匀性,本文使用了维纳滤波技术来实现红外焦平面阵列非均匀校正.该方法首先根据实际情况确定一个输出延迟,然后采用维纳滤波并借助前后帧信息对当前帧进行多次估计,最后取其均值作为此帧的最终校正结果.文中使用了真实红外图像对算法性能进行验证,由于能够充分利用过去和将来的场景信息,因而本算法可以有效地去除原图像上的固定图案噪声.     

非均匀校正技术算法分析与实时系统设计

为获得良好的红外焦平面阵列非均匀校正效果,讨论了非均匀性的来源、噪声类型和目前基于定标,基于场景的常用非均匀校正方法.对修正的时域高通滤波、改进的神经元网络等利用场景信息来估计探测器参数的校正算法进行了仿真效果和实时性能的分析与评价.同时设计了一种以TMS320DM642为处理核心的小型低功耗DSP硬件系统平台,描述了系统流程和实时实现策略,为红外焦平面系统提供了一条有效的实现路径.     

基于边缘检测的神经网络非均匀性校正及硬件实现

红外焦平面探测器的非均匀性校正技术仍然是当前红外热成像系统重点研究的关键技术之一。相对定标类算法,基于场景非均匀性校正根据场景进行非均匀参数更新,不需要使用挡板遮挡视场。本文介绍传统神经网络非均匀性校正算法及加快收敛速度的改进措施,引入边缘检测方法来克服传统神经网络算法的鬼影问题。文中阐述的方法已在以TMS320DM643为处理核心DSP硬件处理平台上实现,取得了较好的校正效果。     

制冷红外焦平面阵列响应特性的研究

文章分析了制冷红外焦平面阵列（IRFPA）的响应模型及响应特性,利用恒温黑体采集某320＊256长波红外焦平面阵列在不同辐射下的响应数据得到其非线性响应曲线,然后讨论分析响应曲线,在实际应用中划分不同的线性响应段,通过调整合适的积分时间结合两点温度定标法对图像的非均匀性进行线性校正,效果良好。     

一种新的红外焦平面器件非均匀性自适应校正算法

红外焦平面阵列（IRFPA）器件普遍存在着响应度的非均匀性问题,而且这种非均匀性随时间和环境改变会发生缓慢变化,目前常用的一次性校正算法不能适应这种变化,同时由于图像场景的多样性,现有的统计校正算法也存在着一定的适应性问题。本文结合图像运动分析中的光流技术,提出了一种新的基于场景的连续校正算法,该算法具有较好的自适应性能。     

微测辐射热计的非均匀性校正新方法

针对微测辐射热计的非均匀性校正对衬底温度要求较高的问题,从探测器的线性模型出发,提出了一种新型非均匀性校正方法。方法首先令阵列中不同探测单元的光响应率比和衬底温度响应率比分别相等,达到补偿衬底温度变化的目的;随后再执行传统的两点非均匀性校正。用数模转换器将存储在EPROM内的偏置电压输出到MOS管的栅极上,实现对偏置电流的控制,调节探测元及补偿元的响应率。仿真结果表明,该校正方法可以在变化范围约为4K的均匀衬底温度内达到良好校正效果。     

一种改进的红外焦平面非均匀性校正算法

针对红外焦平面探测器现有非均匀性校正算法在实际应用中存在的问题,结合实际系统的开发,提出了一种改进算法——一点加两点校正算法。先求两点校正算法的校正增益和校正偏置,再求一点校正算法的校正偏置,求取一点校正算法的偏置参数时的图像数据来自前面求得的两点校正之后的数据,即最后的校正结果是两点校正后的再校正。理论分析和应用表明该算法与目前流行的算法相比具有实时性好、误差小、处理效果好等特点。     

红外焦平面阵列非均匀性嵌入式实时校正技术

红外焦平面阵列（IRFPA）成像是当今红外成像技术发展的主流方向,然而IRFPA特有的非均匀性严重地限制了系统的成像质量。针对红外焦平面阵列在进行非均匀性校正中所涉及的运算量和数据量庞大、实时处理难于实现的特点,本文提出采用高速TMS320C6000系列DSP为核心的嵌入式硬件系统,结合分段线性和分段二次多项式算法,阐述了硬件设计和实现步骤,并给出实验结果,结果表明本系统完全满足实时高精度校正的要求。     

Solution for the nonuniformity correction of infrared focal plane arrays

Based on the S-curve model of the detector response of infrared focal plan arrays (IRFPAs), an improved two-point correction algorithm is presented. The algorithm first transforms the nonlinear image data into linear data and then uses the normal two-point algorithm to correct the linear data. The algorithm can effectively overcome the influence of nonlinearity of the detector's response, and it enlarges the correction precision and the dynamic range of the response. A real-time imaging-signal-processing system for IRFPAs that is based on a digital signal processor and field-programmable gate arrays is also presented. The nonuniformity correction capability of the presented solution is validated by experimental imaging procedures of a 128 x 128 pixel IRFPA camera prototype.     

Scene-based nonuniformity correction with video sequences and registration

We describe a new, to our knowledge, scene-based nonuniformity correction algorithm for array detectors. The algorithm relies on the ability to register a sequence of observed frames in the presence of the fixed-pattern noise caused by pixel-to-pixel nonuniformity. In low-to-moderate levels of nonuniformity, sufficiently accurate registration may be possible with standard scene-based registration techniques. If the registration is accurate, and motion exists between the frames, then groups of independent detectors can be identified that observe the same irradiance (or true scene value). These detector outputs are averaged to generate estimates of the true scene values. With these scene estimates, and the corresponding observed values through a given detector, a curve-fitting procedure is used to estimate the individual detector response parameters. These can then be used to correct for detector nonuniformity. The strength of the algorithm lies in its simplicity and low computational complexity. Experimental results, to illustrate the performance of the algorithm, include the use of visible-range imagery with simulated nonuniformity and infrared imagery with real nonuniformity.     

Scene-based nonuniformity correction technique that exploits knowledge of the focal-plane array readout architecture

Spatial fixed-pattern noise is a common and major problem in modern infrared imagers owing to the nonuniform response of the photodiodes in the focal plane array of the imaging system. In addition, the nonuniform response of the readout and digitization electronics, which are involved in multiplexing the signals from the photodiodes, causes further nonuniformity. We describe a novel scene based on a nonuniformity correction algorithm that treats the aggregate nonuniformity in separate stages. First, the nonuniformity from the readout amplifiers is corrected by use of knowledge of the readout architecture of the imaging system. Second, the nonuniformity resulting from the individual detectors is corrected with a nonlinear filter-based method. We demonstrate the performance of the proposed algorithm by applying it to simulated imagery and real infrared data. Quantitative results in terms of the mean absolute error and the signal-to-noise ratio are also presented to demonstrate the efficacy of the proposed algorithm. One advantage of the proposed algorithm is that it requires only a few frames to obtain high-quality corrections.     

An algebraic algorithm for nonuniformity correction in focal-plane arrays

A scene-based algorithm is developed to compensate for bias nonuniformity in focal-plane arrays. Nonuniformity can be extremely problematic, especially for mid- to far-infrared imaging systems. The technique is based on use of estimates of interframe subpixel shifts in an image sequence, in conjunction with a linear-interpolation model for the motion, to extract information on the bias nonuniformity algebraically. The performance of the proposed algorithm is analyzed by using real infrared and simulated data. One advantage of this technique is its simplicity; it requires relatively few frames to generate an effective correction matrix, thereby permitting the execution of frequent on-the-fly nonuniformity correction as drift occurs. Additionally, the performance is shown to exhibit considerable robustness with respect to lack of the common types of temporal and spatial irradiance diversity that are typically required by statistical scene-based nonuniformity correction techniques.     

便携式 X-射线透视仪图像非均匀性分析及校正

从射线场强度的非均匀性、转换屏响应不一致性和 CCD 相机像元光电响应不一致性三方面对便携式X射线透视仪图像非均匀性的产生机理进行了理论分析. 并在此基础上建立了透视仪每个像元通道光电响应的数学模型. 基于该模型,提出了一种多点线性拟合校正算法. 给出了应用本方法校正前后的图像结果及标准差对比情况. 本方法已应用于便携式安检排爆 X-射线检测系统.     

基于PSO-LSSVM的热电偶非线性校正方法研究

为改善热电偶温度传感器的非线性特性,构建基于粒子群优化算法(particle swarm optimization,PSO)和最小二乘支持向量机(least squares support vector machine,LSSVM)的热电偶非线性校正模型。针对LSSVM算法参数难确定的问题,选用PSO算法搜索LSSVM算法中惩罚系数和核函数参数的最优组合,用优化后的PSO-LSSVM校正模型逼近热电偶的非线性函数关系。为验证该模型的有效性,分别采用BP网络模型、RBF网络模型、LSSVM模型和PSO-LSSVM模型进行热电偶非线性校正,结果表明:PSO-LSSVM模型在热电偶非线性校正应用中表现出最优的稳定性和准确性,其最大拟合误差仅为0.12℃,均方误差为0.0033,准确率达到99.82%。将该模型应用于有限空间爆炸温度的非线性校正中,可取得较好的实际应用效果。     

Comments on “A correction algorithm for detector nonuniformity in computed tomography”

In this paper we comment on the publication “A correction algorithm for detector nonuniformity in computed tomography” by Sun et al. (Nucl. Instr. and Meth. A 505 (2003) 552).     

Generalized algebraic scene-based nonuniformity correction algorithm

A generalization of a recently developed algebraic scene-based nonuniformity correction algorithm for focal plane array (FPA) sensors is presented. The new technique uses pairs of image frames exhibiting arbitrary one- or two-dimensional translational motion to compute compensator quantities that are then used to remove nonuniformity in the bias of the FPA response. Unlike its predecessor, the generalization does not require the use of either a blackbody calibration target or a shutter. The algorithm has a low computational overhead, lending itself to real-time hardware implementation. The high-quality correction ability of this technique is demonstrated through application to real IR data from both cooled and uncooled infrared FPAs. A theoretical and experimental error analysis is performed to study the accuracy of the bias compensator estimates in the presence of two main sources of error.