阵列相机多光谱图像采集技术

过去几年里,开展了大量的多光谱图像采集领域的研究工作,但主要采用的是轮盘变换式的多光谱图像采集系统。近来,一种新的多光谱图像采集方法被提出,基于阵列相机延伸范围来形成多个通道,因此引入多光谱阵列相机的概念。本文构造基于阵列相机的多光谱图像采集系统。该阵列相机采用12个大恒DH-HV1300FM型相机,11个镜头装有波长不同的滤光片。本文结合阵列相机多通道数的优势,提出一种光谱反射率重建算法,能够可靠并有效地重建场景的光谱反射率。仿真实验结果验证了该系统的有效性。     

基于颜色自适应字典的双相机光谱系统重建算法

通过将快照编码孔径光谱成像和普通RGB彩色成像结合,双相机光谱成像系统能够高效地获取场景的光谱信息,具有广阔的应用前景.如何高质量地从压缩采样中重建高光谱图像是该系统需要解决的重要问题.根据高光谱图像与彩色图像在空间结构和光谱响应上的相关性,本文了提出一种基于颜色自适应字典的重建算法,用以提高双相机光谱成像系统的重建质量.首先,利用RGB观测分别训练三通道非负字典.然后,以彩色相机的光谱响应曲线为指导,为每一个谱带选择光谱相关性最大的字典.最后,完成高光谱图像的稀疏重建.高光谱数据库和遥感数据库的仿真结果均表明,本文提出的算法能够大幅度提升双相机光谱成像系统的重建质量.     

基于单片机的光谱反射率试验台

介绍了一种由MCS-51单片机实现的数字化后视镜光谱反射率试验台，着重讨论了系统的硬件设计，并研制了光谱反射率试验台。文章最后进行了误差分析，给出的试验数据表明，该设计是合理有效的。     

低成本便携式多光谱成像系统的研发及优化

目的 针对现有多光谱成像系统存在成本高、结构复杂、操作难度大和响应速度慢等问题。因此，本文提出了一种基于脉冲调制的低成本便携式多光谱成像系统，并采用客观图像质量评估（image quality assessment，IQA）的方法对其系统参数进行优化。方法 该系统主要由光源模块、控制模块、图像采集模块和图像分析模块4部分组成。光源模块采用9个波长的LED （light emitting diode）阵列，其中心波长为365 nm、390 nm、460 nm、515 nm、585 nm、620 nm、650 nm、730 nm和840 nm；控制模块主要包括LED驱动电路和USB （universal serial bus）电源，可以通过发送一定时间间隔的脉冲波来分时点亮LED，并通过一定阻抗匹配使LED发光强度达到最大值；图像采集模块主要使用去除红外截止滤波片的高清红外工业相机，该相机的最佳光谱感应范围包含所选的9个LED灯珠的中心波长；图像分析模块主要执行客观图像质量评估算法。系统执行时，STC89C51单片机发射周期为T的脉冲波来驱动9种不同波长的LED分时点亮。然后，计算机平台调用高清红外相机模组，以相匹配的间隔捕获多光谱图像。在系统拍摄参数优化实验中，本文采用模糊度和清晰度评价指标对所获得的多光谱图像从相机拍摄时间间隔、相机拍摄距离和光照强度3个角度进行质量评估，进而获得较优的系统成像参数。结果 通过改变系统拍摄参数，对3个场景下的不同拍摄条件所获取的多光谱图像质量进行评估，结果显示：对于本文所搭建的多光谱成像系统，相机拍摄时间间隔与LED灯珠频闪周期同步，拍摄距离为25 mm，光照强度为45 Lux下成像质量相对较好。结论 本文设计并搭建的基于脉冲调制的低成本便携式多光谱成像系统成本低、操作难度小、结构简单、成像质量较好、成像速度较快，可以满足多光谱成像系统大规模推广使用的要求。此外，本文的系统设计方法、设计思路和实验方案等可以为后续研究提供借鉴。     

定西遥感试验场土壤光谱特征分析

对分布于甘肃省东部的黑壤土、灰褐土、黄绵土、新积土4个土类的7个土属进行电磁波谱测试。在0.4～1.1μm波段内,以土种为单位共测试21条裸土光谱曲线。从形态上可区分为缓斜型和陡坎型。在0.4～0.65μm波段内,各土壤光谱反射率值多相互交错分布,但在0.65～1.1μm波段内,陡坎型类土壤的光谱反射率值多高于缓斜型。土壤表层质地差异大时,将影响电磁波辐射能量的变化,当土壤表层水分含量小于饱和含水量时,在0.55～0.95μm波段内,土壤水分含量越高,其光谱反射率值越低。经各波段与反射率之间的相关分析说明,缓斜型土壤光谱曲线以一元一次回归曲线拟合程度高,而陡坎型土壤则以一元二次回归曲线拟合更为理想。该结果为在遥感图像中提取土壤线信息,提供了可参考的数据。     

褐潮土的光谱特性及用土壤反射率估算有机质含量的研究

本文通过ASDFR便携式光谱仪对132个风干土壤样品的光谱反射率进行了实验室测定。根据土样光谱反射率变化,获得了褐潮土土壤剖面的不同诊断层反射光谱特征。结果表明,在400～1200nm范围之间,土壤有机质含量与土壤光谱反射率有较好的相关性。利用导数光谱方法建立了预测土壤有机质含量的方程,提出了预测北京地区褐潮土有机质光谱的最佳波段。在波长447nm处采用反射率和A值(反射率倒数的对数)所建立的预测方程的预测精度较高。采用反射率的一阶微分建立的预测方程的最佳波段在516nm处。而A值一阶微分光谱在615nm处相关性最好。作为一项参考指标用光谱分析法评价土壤中有机质含量,以期对精准农业中土壤养分或肥力的预测具有一定的指导作用。     

松毛虫危害的光谱特征与虫害早期探测模式

根据生态学特征，本文将松毛虫危害的针叶样品分为５个等级，对其反射光谱和叶绿素含量进行了测量分析。结果表明，随受害程度加重，叶绿素含量降低，５５０ｎｍ处的反射率、近红外肩反射率与红光最低反射率之差及红界一阶导数谱最大值均呈下降趋势，６３０ｎｍ处反射率呈上升趋势，红界光谱蓝移、叶绿素反射峰红移明显。应用逐步判别分析法对比分析证实了细分光谱特征参量比绿、红、近红外三波段反射率参量有更强的判别分类能力，这     

南京冬季典型植被光谱特征分析

利用FieldSpec4便携式地物光谱仪和ASD积分球,于2014年7月和12月对研究区6种典型植被进行光谱数据采集与处理,分析植被冠层和落叶的光谱特征及其变化规律,同时分析坡度因素、测量方法对植被光谱反射率的影响。结果表明:不同季节常绿植被光谱存在差异,不同植被光谱反射率的季节变化也不同。冬季常绿植被具有相似的光谱特征,但是不同植被类型之间也存在明显的差异。冬季植被冠层光谱呈现出先降低后稳定的特点;植被落叶层光谱由于受叶片色素、含水量、土壤背景等因素的影响,在衰老腐化的过程中并未出现明显的规律性变化。一定坡度范围内,植被光谱反射率随坡度的增大而升高。不同的测量方法获取的植被光谱反射率不同,但是光谱变化规律相同。     

模拟酸雨对水稻叶片反射光谱特性影响的初步研究

本文研究了模拟酸雨对水稻叶片反射光谱特性的影响。结果表明：模拟酸雨会引起水稻叶片反射光谱的可见光区和中红外区的反射率升高，近红外区的反射率降低，相应的反射率比值也随之变化，一阶和二阶微分光谱蓝移，且上述变化的程度与酸雨的酸度，水稻的品种和生育期有关。这一结果也表明遥感技术监测酸     

裸土表层含水量高光谱遥感的最佳波段选择

在自然状况下，对裸土进行人为干湿处理，利用ASD PRO FR2500地物光谱仪测得土壤在350nm～2500nm反射光谱并适时采取表层土，利用烘干法测得土壤体积含水量。依据土壤湿度与土壤光谱反射率之间的相关关系，得出土壤含水量与土壤光谱反射率的非线性方程。利用该方程和光谱反射率值进行土壤水分反演，通过对反演结果的误差分析，结合光谱反射率与体积含水量的指数回归分析，笔认为采用1950nm～2250nm波段的光谱反射率估测土壤含水量效果较好。     

数码印染业中的光谱颜色量化

印染业中,用测色仪器测量颜色及传统颜色测量方法存在着测色精度低、测量速度慢、测量效果依赖于设备等不足,基于此问题,通过对物体颜色光谱特性的研究,提出一种数学模型结合扫描仪或数码相机等数字图像输入设备的光谱颜色定量化方法,首先经扫描仪／照相机获取物体的颜色信息,在此基础上,利用多项式模型预测各个像素RGB值对应的XY-ZLMS值,再通过光谱重构算法,将XYZLMS值转化为光谱反射比,最终用光谱反射比来对颜色进行表征量化。实验过程选用自制色卡为样本,对整个颜色量化过程进行数据分析和仿真,结果证明：该方法克服了测色仪器测量及传统颜色测量方法上的不足之处,达到了颜色测量的高精度,快捷,方便和多样化的需求。     

Color from black and white

Color constancy can be achieved by analyzing the chromatic aberration in an image. Chromatic aberration spatially separates light of different wavelengths and this allows the spectral power distribution of the light to be extracted. This is more information about the light than is registered by the cones of the human visual system or by a color television camera; and, using it, we show how color constancy, the separation of reflectance from illumination, can be achieved. As examples, we consider grey-level images of (a) a colored dot under unknown illumination, and (b) an edge between two differently colored regions under unknown illumination. Our first result is that in principle we can determine completely the spectral power distribution of the reflected light from the dot or, in the case of the color edge, the difference in the spectral power distributions of the light from the two regions. By employing a finite-dimensional linear model of illumination and surface reflectance, we obtain our second result, which is that the spectrum of the reflected light can be uniquely decomposed into a component due to the illuminant and another component due to the surface reflectance. This decomposition provides the complete spectral reflectance function, and hence color, of the surface as well as the spectral power distribution of the illuminant. Up to the limit of the accuracy of the finite-dimensional model, this effectively solves the color constancy problem.     

Practical Measurement and Reconstruction of Spectral Skin Reflectance

We present two practical methods for measurement of spectral skin reflectance suited for live subjects, and drive a spectral BSSRDF model with appropriate complexity to match skin appearance in photographs, including human faces. Our primary measurement method employs illuminating a subject with two complementary uniform spectral illumination conditions using a multispectral LED sphere to estimate spatially varying parameters of chromophore concentrations including melanin and hemoglobin concentration, melanin blend-type fraction, and epidermal hemoglobin fraction. We demonstrate that our proposed complementary measurements enable higher-quality estimate of chromophores than those obtained using standard broadband illumination, while being suitable for integration with multiview facial capture using regular color cameras. Besides novel optimal measurements under controlled illumination, we also demonstrate how to adapt practical skin patch measurements using a hand-held dermatological skin measurement device, a Miravex Antera 3D camera, for skin appearance reconstruction and rendering. Furthermore, we introduce a novel approach for parameter estimation given the measurements using neural networks which is significantly faster than a lookup table search and avoids parameter quantization. We demonstrate high quality matches of skin appearance with photographs for a variety of skin types with our proposed practical measurement procedures, including photorealistic spectral reproduction and renderings of facial appearance.     

Wide Gamut Spectral Upsampling with Fluorescence

Physically based spectral rendering has become increasingly important in recent years. However, asset textures in such systems are usually still drawn or acquired as RGB tristimulus values. While a number of RGB to spectrum upsampling techniques are available, none of them support upsampling of all colours in the full spectral locus, as it is intrinsically bigger than the gamut of physically valid reflectance spectra. But with display technology moving to increasingly wider gamuts, the ability to achieve highly saturated colours becomes an increasingly important feature. Real materials usually exhibit smooth reflectance spectra, while computationally generated spectra become more blocky as they represent increasingly bright and saturated colours. In print media, plastic or textile design, fluorescent dyes are added to extend the boundaries of the gamut of reflectance spectra. We follow the same approach for rendering: we provide a method which, given an input RGB tristimulus value, automatically provides a mixture of a regular, smooth reflectance spectrum plus a fluorescent part. For highly saturated input colours, the combination yields an improved reconstruction compared to what would be possible relying on a reflectance spectrum alone. At the core of our technique is a simple parametric spectral model for reflectance, excitation, and emission that allows for compact storage and is compatible with texture mapping. The model can then be used as a fluorescent diffuse component in an existing more complex BRDF model. We also provide importance sampling routines for practical application in a path tracer.     

Thermal cameras and applications: a survey

Thermal cameras are passive sensors that capture the infrared radiation emitted by all objects with a temperature above absolute zero. This type of camera was originally developed as a surveillance and night vision tool for the military, but recently the price has dropped, significantly opening up a broader field of applications. Deploying this type of sensor in vision systems eliminates the illumination problems of normal greyscale and RGB cameras. This survey provides an overview of the current applications of thermal cameras. Applications include animals, agriculture, buildings, gas detection, industrial, and military applications, as well as detection, tracking, and recognition of humans. Moreover, this survey describes the nature of thermal radiation and the technology of thermal cameras.     

Spectralization: Reconstructing spectra from sparse data

Traditional RGB reflectance and light data suffers from the problem of metamerism and is not suitable for rendering purposes where exact color reproduction under many different lighting conditions is needed. Nowadays many setups for cheap and fast acquisition of RGB or similar trichromatic datasets are available. In contrast to this, multi‐ or even hyper‐spectral measurements require costly hardware and have severe limitations in many cases. In this paper, we present an approach to combine efficiently captured RGB data with spectral data that can be captured with small additional effort for example by scanning a single line of an image using a spectral line‐scanner. Our algorithm can infer spectral reflectances and illumination from such sparse spectral and dense RGB data. Unlike other approaches, our method reaches acceptable perceptual errors with only three channels for the dense data and thus enables further use of highly efficient RGB capture systems. This way, we are able to provide an easier and cheaper way to capture spectral textures, BRDFs and environment maps for the use in spectral rendering systems.     

基于支持向量回归的光谱反射率重建方法

提出了一种基于支持向量回归和小框架核的光谱反射率重建方法。光谱反射率重建是光学研究的一个重要问题,其目的是通过各种成像设备所获取的与设备相关的RGB三色值重建出物体本身固有的与设备和光照都无关的光谱反射率。回归方法已经在这一领域取得了广泛应用,如基于多项式模型的正则化最小二乘方法、基于核的正则化最小二乘方法等。提出了一种新的光谱反射率重建方法,这种方法采用了一种可以减弱样本不规则噪音影响的小框架核函数,并将其用于支持向量回归来重建光谱反射率函数。实验表明,新方法可以提高光谱反射率重建的精度和稳定性。     

Hyperspectral-cube-based mobile face recognition: A comprehensive review

With the hyperspectral sensor technology evolving and becoming more cost-effective, hyperspectral imaging offers new opportunities for robust face recognition. Hyperspectral face cubes contain much more spectral information than face images from common RGB color cameras. Hyperspectral face recognition is robust to the impacts, such as illumination, pose, occlusion, and spoofing, which can heavily avoid the limitations of the visible-image-based face recognition.In this paper, we summarize the spectrum properties of hyperspectral face cubes and survey the hyperspectral face recognition methods in the literature. We categorize them into major groups for better understanding. We overview the existing hyperspectral face datasets, and establish our own dataset. We also discuss efficient neural networks used for mobile face recognition and conduct experiments on mobile hyperspectral face recognition. Results show that under harsh conditions like large illumination changing and pose variation, hyperspectral-cube-based methods have higher recognition accuracy than visible-image-based methods. Finally, we deliver insightful discussions and prospects for future works on mobile hyperspectral face recognition.     

Acquisition of High Spatial and Spectral Resolution Video with a Hybrid Camera System

We present a hybrid camera system for capturing video at high spatial and spectral resolutions. Composed of an red, green, and blue (RGB) video camera, a grayscale video camera and a few optical elements, the hybrid camera system simultaneously records two video streams: an RGB video with high spatial resolution, and a multispectral (MS) video with low spatial resolution. After registration of the two video streams, our system propagates the MS information into the RGB video to produce a video with both high spectral and spatial resolution. This propagation between videos is guided by color similarity of pixels in the spectral domain, proximity in the spatial domain, and the consistent color of each scene point in the temporal domain. The propagation algorithm, based on trilateral filtering, is designed to rapidly generate output video from the captured data at frame rates fast enough for real-time video analysis tasks such as tracking and surveillance. We evaluate the proposed system using both simulations with ground truth data and on real-world scenes. The accuracy of spectral capture is examined through comparisons with ground truth and with a commercial spectrometer. The utility of this high resolution MS video data is demonstrated on the applications of dynamic white balance adjustment, object tracking, and separating the appearance contributions of different illumination sources. The various high resolution MS video datasets that we captured will be made publicly available to facilitate research on dynamic spectral data analysis.