Iterative sparse reconstruction of spectral domain OCT signal

We propose and study an iterative sparse reconstruction for Fourier domain optical coherence tomography （FD OCT） image by solving a constrained optimization problem that minimizes L-1 norm. Our method takes the spectral shape of the OCT light source into consideration in the iterative image reconstruction procedure that allows deconvolution of the axial point spread function from the blurred image during reconstruction rather than after reconstruction. By minimizing the L-1 norm, the axial resolution and the signal to noise ratio of image can both be enhanced. The effectiveness of our method is validated using numerical simulation and experiment.     

Optimized basis function for spectral reflectance recovery from tristimulus values

Spectral reflectance is a significant physical property of materials. It plays an important role in color constancy, illumination modeling, and color reproduction. Spectral reflectance basis functions are the most important impact factors for spectral reflectance recovery. Previous methods mainly calculated basis functions for the reflectance spectra data sets by employing the principle component analysis (PCA) and its improved methods. In this paper, we present a new method to solve this problem. Specifically, we propose a new cost function and some constraint conditions to convert the problem into an optimization problem by minimizing the cost function. Unlike the PCA method which yields the orthogonal basis functions for approximating the reflectance spectra, our method yields the nonorthogonal basis functions for better approximating the reflectance spectra. Experimental results show that our derived basis functions are better than those obtained by the PCA method for reflectance spectra recovery.     

基于优化迭代算法的细胞荧光光谱解析

使用光谱测量方法进行细胞多色荧光分析时, 发射光谱会产生部分光谱重叠, 为定性和定量分析造成了一定的困难。为此, 提出基于优化迭代算法的细胞荧光光谱解析算法, 建立重叠峰模型并确定单峰顶点; 根据每次构造峰面积的大小, 重新确定构造峰的构造方式, 最终得到模拟峰的顶点及面积信息。利用该算法对高斯函数叠加形成的重叠峰进行解析, 并与常规方法进行对比, 结果表明优化迭代算法解析误差稳定在0.15%以内; 加入随机噪声后, 解析误差可稳定在0.85%以内, 均优于另外两种算法。此外, 计算了该算法下的迭代效率, 结果表明该算法较常规方法提高了32.2%。     

Iterative atmospheric correction scheme and the polarization color of alpine snow

Characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of a few geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of these measurements is overwhelmed by that of instruments with polarization capabilities: proposed models in this case are based on the Fresnel reflectance of an isotropic distribution of facets. Because of its remarkable lack of spectral contrast, the polarized reflectance of land surfaces in the shortwave infrared spectral region, where atmospheric scattering is minimal, can be used to model the surface also at shorter wavelengths, where aerosol retrievals are attempted based on well-established scattering theories.In radiative transfer simulations, straightforward separation of the surface and atmospheric contributions is not possible without approximations because of the coupling introduced by multiple reflections. Within a general inversion framework, the problem can be eliminated by linearizing the radiative transfer calculation, and making the Jacobian (i.e., the derivative expressing the sensitivity of the reflectance with respect to model parameters) available at output. We present a general methodology based on a Gauss–Newton iterative search, which automates this procedure and eliminates de facto the need of an ad hoc atmospheric correction.In this case study we analyze the color variations in the polarized reflectance measured by the NASA Goddard Institute of Space Studies Research Scanning Polarimeter during a survey of late-season snowfields in the High Sierra. This insofar unique dataset presents challenges linked to the rugged topography associated with the alpine environment and a likely high water content due to melting. The analysis benefits from ancillary information provided by the NASA Langley High Spectral Resolution Lidar deployed on the same aircraft.The results obtained from the iterative scheme are contrasted against the surface polarized reflectance obtained ignoring multiple reflections, via the simplistic subtraction of the atmospheric scattering contribution. Finally, the retrieved reflectance is modeled after the scattering properties of a dense collection of ice crystals at the surface. Confirming that the polarized reflectance of snow is spectrally flat would allow to extend the techniques already in use for polarimetric retrievals of aerosol properties over land to the large portion of snow-covered pixels plaguing orbital and suborbital observations.     

局部k最近邻加权线性回归的光谱反射率重建

现实中很多场景都需要精确的颜色表示,如纺织、印刷、艺术品扫描存档、在线商品展示等。光谱反射率是决定物体颜色的本质属性,如果知道了光谱反射率,就可以重现物体在任何光照和观测条件下的颜色。采用专业仪器测量光谱反射率有成本高、分辨率低、测量时间慢等问题。随着数码成像设备的普及,基于相机RGB响应值的光谱反射率重建算法具有重要现实意义。光谱反射率重建的目的是建立低维RGB响应值到高维光谱反射率向量的映射关系,回归方法在这一领域已取得广泛应用。由于光谱反射率向量所处的空间是嵌在高维欧氏空间中的一个低维子流形,在训练样本有限的条件下,传统的全局回归方法不能有效地学习该流形结构,往往导致过拟合,使得学习出来的模型泛化能力较差。局部线性回归方法虽然可以改善全局回归过拟合的问题,但是局部学习方法易受例外点的影响,导致拟合不足。针对这一问题,提出一种基于局部加权线性回归的光谱反射率重建方法,这种方法在一个k最近邻范围约束内,给每个局部训练样本赋予不同的权重,从而有所侧重地利用局部训练样本来估计光谱反射率。实验结果表明,基于局部k最近邻加权线性回归的方法能更有效地利用局部信息,缓解过拟合和拟合不足,更准确地重建光谱反射率。     

基于彩色数字相机的光谱反射率重建方法研究

如何在给定照明条件和观测条件的情况下,由彩色数字相机的响应值重建物体表面光谱反射率,仍是颜色科学与工程领域一个尚待解决的重要课题。文章使用奇异值分解的方法将光谱反射率近似为若干基向量的线性组合,求得组合系数,然后使用相机输出数据与组合系数训练人工神经网络,使之能够准确的模拟相机输出与组合系数之间的非线性关系,最后采用经训练的神经网络,与基向量结合,由相机输出准确的重建物体表面的光谱反射率。实验结果显示,与线性近似的方法相比,使用该方法对标准Munsell色块进行反射率重建,重建误差减小了约67%,具有高精度、易实现、易操作的特点,可用于对重建精度要求较高的诸多领域。     

基于光谱连接空间的彩色相机光谱重构研究

针对彩色相机三通道响应值重构光谱反射率精度低的问题,提出了基于光谱连接空间的彩色相机光谱反射率重构方法。首先通过光谱反射率已知的训练样本集和多项式拟合方法建立相机响应值到光谱连接空间的转换矩阵,然后利用该矩阵将待重构样本的相机响应值映射到光谱连接空间,最后选用合适的光谱重构算法在光谱连接空间内实现光谱反射率重构,并利用色度误差和光谱误差两个指标对重构结果进行评价。在上述过程中,鉴于转换矩阵的重要性,采用了基于反距离加权的最小二乘法计算转换矩阵以提高相机响应值到光谱连接空间的转换精度。实验结果表明:本文方法切实可行且精度可靠,与基于彩色相机三通道响应值的光谱重构方法相比,色度重构精度和光谱重构精度均显著提高,平均色差和谱差分别为1.145 2和0.010 3,可在较大程度上满足数字典藏、高保真颜色复制等的需要。     

Spectral response data for development of cool coloured tile coverings

Most ancient or traditional buildings in Italy show steep-slope roofs covered by red clay tiles. As the rooms immediately below the roof are often inhabited in historical or densely urbanized centres, the combination of low solar reflectance of tile coverings and low thermal inertia of either wooden roof structures or sub-tile insulation panels makes summer overheating a major problem. The problem can be mitigated by using tiles coated with cool colours, that is colours with the same spectral response of clay tiles in the visible, but highly reflecting in the near infrared range, which includes more than half of solar radiation. Cool colours can yield the same visible aspect of common building surfaces, but higher solar reflectance.Studies aimed at developing cool colour tile coverings for traditional Italian buildings have been started. A few coating solutions with the typical red terracotta colour have been produced and tested in the laboratory, using easily available materials. The spectral response and the solar reflectance have been measured and compared with that of standard tiles.     

基于同色异谱黑理论的非线性复合模型光谱重建研究

同色异谱现象是光谱反射率重建与颜色再现中的一个重要问题。采用三基色CCD相机采集CIE标准光源D65下的颜色样品信号,建立非线性复合模型,使用主成分分析结合神经网络的方法(PCA-NET)改进基于同色异谱黑理论的R矩阵算法,对标准Munsell色卡光谱重建进行研究。在保证给定照明条件下的色度精度同时,对光谱重建的结果进行了实验评价和讨论。实验结果表明,在给定的照明条件下,PCA-NET算法能够准确的拟合相机输出信号与主成分系数之间的非线性关系, 将其代替线性算法应用于R矩阵算法中时,测试集的平均均方根值是未改进R矩阵算法的0.76,平均标准差是R矩阵算法的0.85,可有效提高光谱反射率的重建精度。改进后的R矩阵算法具有精度较高、操作简单易实现的特点, 可用于对重建色度精度及光谱精度均要求较高的领域。     

土壤水分去除算法的田间原位光谱反演棉田有机质

田间原位可见-近红外光谱(VIS-NIR)能够有效的提高土壤属性的检测效率,但由于原位土壤中水分因素的影响,土壤属性的预测精度很难达到预期。如何有效去除土壤中的水分对土壤其他属性光谱预测的影响,是利用田间原位光谱高精度预测土壤属性所面临的难题,也是土壤光谱技术由室内转向田间的突破口。该问题的有效解决,可减除土壤样品的采集与室内预处理等过程,实现土壤属性的田间原位光谱测定。以新疆南部地区阿拉尔垦区十二团棉田为研究区,采用网格采样法共采集了116个0～20 cm深度的表层土壤样品,剔除1个异常值样品,得到115个有用样品,利用SR-3500型便携式地物光谱仪采集了231个样点的田间原位光谱数据,土样经风干、研磨和过筛等处理后测定其室内光谱和有机质含量。利用Kennard-Stone算法将115个土样分为69个转换子集及46个预测集,采用外部参数正交化法(EPO)、光谱直接转换法(DS)及光谱间接转换法(PDS)三种去除水分算法结合原位光谱反射率(R)、反射率一阶微分(R′)、反射率对数(LOG(R))以及反射率倒数(1/R)四种数学变换方式,运用随机森林(RF)模型进行不同组合模型的构建及精度评价。结果表明：(1)土壤有机质含量越高,土壤光谱反射率越低。土壤田间原位光谱反射率低于土壤室内光谱反射率;(2)室内光谱反射率与土壤有机质含量之间的相关性大于田间原位光谱,室内光谱经一阶微分变换后与土壤有机质含量之间的相关性显著提升。(3)土壤室内光谱反射率模型预测精度(R2=0.86, RPD=2.08, RMSE=1.55 g·kg-1, MAPE= 0.14)高于田间原位光谱反射率模型(R2=0.71, RPD=1.49, RMSE=2.17 g·kg-1, MAPE=0.20)。在去除水分算法模型中,以EPO一阶微分模型去除水分效果最好,决定系数R2由0.71提高到0.83,RPD由1.49提高到2.04,RMSE由2.17 g·kg-1降低至1.58 g·kg-1,MAPE由0.20降低至0.14。本研究实现了去除土壤水分因素的影响,提高了田间原位光谱预测土壤有机质的精度,为南疆棉田大尺度土壤有机质的预测及土壤肥力的评价提供了重要的参考。     

基于比较测量法的LCTF光谱相机光谱反射率重建研究

基于液晶调谐滤光片(LCTF)的光谱相机由于体积小、功耗低、集成方便,适合多种搭载平台,同时通过光谱反射率来识别目标物,可以有效解决同色异谱的问题,在伪装识别、精细农产品产值估计等方面有很好的应用前景。比较测量法因其能有效排除光照条件和场景背景条件的影响,重建效率较高,在光谱相机的光谱反射率重建中被普遍采用。比较测量法通常采用标准白板作为参考物,但实际应用中,经常会遇到目标场景空间位置不便放置标准白板的情况。针对这种情况,研究采用LCTF光谱相机采集的目标场景中亮度高的颜色作为参考的比较测量法进行目标物的光谱反射率重建来解决上述问题。实验以美国X-Rite的Gretg Macbeth Color Checker(MCC)色卡作为目标物,分别参考亮度高的五个不同色块,运用比较测量法完成红、绿、蓝三个色块的光谱反射率重建。将重建后三个色块的光谱反射率与采用台式分光光度计(X-Rite Color Eye7000A)测量的标准光谱反射比进行比较。结果显示,重建后的红、绿、蓝三个色块的光谱反射率曲线与用分光光度计测量的标准光谱反射率曲线的形状基本相似,每组曲线的均方根误差均小于0.05;重建的蓝色色块的光谱反射率以参考与其光谱反射比接近的蓝绿色重建的效果最好;重建的红色和绿色色块的光谱反射率以除白色外亮度最高的黄色为参考重建的效果最好;二者均比参考标准白板的反射率重建效果好。实验结果说明采用目标场景中亮度高目视效果明显的色块作为参考对象可被用来进行LCTF光谱相机的光谱反射率重建。该方法有效扩大了比较测量法以及液晶调谐光谱成像系统的应用效率。     

Spectral characterization of black materials for use as background in spectrometric laboratories

This paper describes a study aimed at the assessment of low-reflectance equipment in a laboratory using spectral measurements. The use of reflectance spectrometers is common for the detection of soils, minerals, vegetation, and manmade materials, but comparability remains questionable. It is well-known that several factors can have profound effects on measured reflectance spectra. In this paper, we present a low-reflectance material that eliminates the impact of light effects from sample backgrounds or the equipment and walls of dark chambers. For laboratory spectral measurements, two different setups (changes in geometry) of the experimental design with ASD FieldSpec Pro were performed. Overall, 23 visible black materials were measured. Statistical analysis revealed that only three materials were useful for the investigated topic. These materials (foam rubber, cellulose fleece, and thermal coating) exhibit low reflection, below 10%, are flat and featureless in the spectral curve and have low spectral variation by rotation. In contrast, 20 other materials showed either low reflectance in visible light, a high spectral variation by rotation or in the second setup, high specular radiation. The results indicated that in certain cases, laboratory reflectance measurements made by a non-qualified background material were not truly reproducible or suitable for a spectral library. This experiment demonstrates a problem in laboratory scenarios involving remote sensing working groups, helps to place our measurements in context, and forms the basis for comparison with other studies.     

Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image

In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.     

Limitation of Color Samples for Spectral Estimation from Sensor Responses in Fine Art Painting

A new technique is proposed to improve the way of selecting samples used to estimate spectral reflectance from sensor responses in multi-band images. This technique limits the samples of reflectance spectra based on the spectral reflectance estimated by the conventional estimation method, and estimates it again using the limited samples. Vector angle and distance among reflectance spectra as the criteria for the limitation can be applied to improve the estimation of reflectance spectra.     

粗糙目标样片光谱双向反射分布函数的实验测量及其建模

实验测量了紫红色和白色涂漆板在400～780 nm内的光谱双向反射分布函数(光谱BRDF),分析了光谱双向反射分布函数随波长及散射角的变化趋势与目标样片光学特性的关系.应用改进的粒子群算法,结合双向反射分布函数五参量模型,获得了测量光谱范围内各波长(间隔1 nm)对应的共381组五参量值.利用五参量模型计算了目标样片的光谱双向反射分布函数及其方向半球反射率(DHR),并与实验测量数据相比较,两者吻合良好,表明目标光谱双向反射分布函数建模方法与结果的可行性和可靠性.目标样片的光谱双向反射分布函数可以用来研究目标的光谱散射特性,对目标的探测、跟踪、识别和特征提取等具有重要的应用价值.     

基于函数拟合的玉米叶片反射光谱时间变化规律分析

为了探索玉米(Zea mays L.)叶片反射光谱时间变化规律,对21个叶位的玉米叶片进行了每天一次的反射光谱测量,获得了玉米活体叶片整个生命周期反射光谱数据1 261条。在此基础上采用光谱相关图方法,对400～960 nm的可见光、近红外波段的玉米叶片反射光谱进行分段拟合,获得了7个表征玉米叶片反射光谱时间变化规律的拟合参数,并对这7个参数的时间变化趋势采用二元二次多项式进行拟合。结果表明该方法对单片叶片反射光谱的拟合效果非常理想,其中98.7%的叶片反射光谱拟合复相关系数r大于0.99,80.9%的叶片反射光谱拟合均方根误差RMSE小于0.001 5。将所有数据的拟合结果与原始数据进行比较,复相关系数r为0.9978,均方根误差RMSE为0.010 5,拟合结果表明该方法较好地保持了反射光谱时间变化的趋势,能够充分利用叶片反射光谱的相关性,有效地表征玉米叶片反射光谱随时间变化的规律。     

旁瓣约束下期望主瓣幅度响应迭代波束设计

研究了旁瓣约束下的期望主瓣幅度逼近问题,其包含双边绝对值不等式结构,为非凸波束设计问题。针对传统的多约束优化算法难以处理非凸结构,提出了两种迭代算法。一种对原优化问题作局域线性近似,将非凸约束转换为仿射约束,进而迭代局部二阶锥规划问题求解原问题。另一种通过引入辅助变量构建增广拉格朗日函数,将加权向量与各约束解耦合,交替迭代求解关于原变量、主瓣辅助变量与旁瓣辅助变量的三个子优化问题以给出初始非凸问题的解。针对子优化问题,通过灵活运用拉格朗日乘子技术构建了低复杂度求解方案。采用仿真和实测阵列流形验证设计效果,结果表明,所提两种迭代算法可实现主瓣幅度逼近,合成平顶波束图,且对阵型无依赖性。交替迭代法耗时显著低于迭代二阶锥规划法。      

光照光谱功率分布的估计和颜色分割

提出了应用有限维线性模型和双色反射模型和双色反射模型抽表示而物体颜色的本征特性的方法，首先估计出光照的光谱功率分布，再获取物体的表面光谱反射率，从而得到和光照与几何条件无关的归一化偏差光谱反射率，它仅反映物体的表面反射特性，可作为颜色分割和识别的可靠特征。     

基于迭代Tikhonov正规化的三刺激值重建光谱方法研究

光谱图像中的反射率光谱数据维数高,且与光源、设备均无关,能够比较全面、真实、客观地描述图像中物体的颜色信息。针对三色相机的光谱图像获取系统中三维色度数据重建多维光谱数据产生的光谱信息丢失、以及伴随而生的颜色信息丢失问题,提出了迭代Tikhonov正规化的光谱重建方法。首先依据色度学理论中色度值与反射率光谱之间的关系,构建反射率光谱重建方程建立起相机所获三维色度数据与高维反射率光谱数据的映射关系;然后,通过反射率光谱重建方程的病态分析,在Moore-Penrose伪逆矩阵求解思想的基础上构建迭代Tikhonov正规化方法求解反射率光谱,并利用训练样本数据通过L-曲线方法训练获取迭代Tikhonov正规化的最优正规化参数,以有效控制并改善反射率光谱重建方程求解的病态、减少重建光谱的光谱信息丢失。实验通过选取样本数据对光谱重建方法进行验证。验证实验的结果表明所提出的光谱重建方法改善了三色相机的光谱图像获取系统中重建光谱的光谱信息丢失程度,使得重建光谱的光谱误差和色度误差较其他光谱重建方法均有明显降低。     

双边缘技术多普勒测风激光雷达标准具的优化

 优化了基于双边缘技术的直接测风多普勒激光雷达中F-P标准具的工作参数。确定激光谱宽后，选择适当的F-P标准具自由谱间距，可正确消除瑞利背景噪声的影响。分析了标准具镜面缺陷、非严格平行和入射光束发散角对其透过率曲线的影响。将标准具透过率函数表达为唯一系统参数，即反射精细度的函数；通过计算散粒噪声极限时的相对测量误差，可确定最优反射精细度以及激光频率相对标准具透过率中心频率的最佳偏置；由最优反射精细度可得到入射到标准具光束的最大发散角和标准具的最小通光口径。