Optimal color filters in the presence of noise

The effect of noise on the number of effective channels (color filters) used to record a color image is investigated. Transmittances of color filters are calculated that minimize the mean square error that occurs when estimating, from the recorded data, the colors in the image under a collection of viewing illuminants. Since the results indicate that a significant improvement in color correction accuracy is achieved by using four channels, there is good reason to consider using four-tuples for representation of colorimetric information.     

Filter considerations in color correction

The quality of color correction is dependent on the filters used to scan the image. This paper introduces a method of selecting the color filters using a priori information about the viewing illuminants. Color correction results using the derived filters are compared with color correction results using filters that are optimal for individual viewing and recording illuminants. The comparison is performed using the CIE PEL (L*a*b*) perceptual color difference measure. Applications of this work are found in the design of scanners, copiers, and television systems.     

Recovery of spectral reflectances of objects being imaged without prior knowledge.

Prior knowledge of the noise present in a color image acquisition device is very important in estimating colorimetric values or in recovering the spectral reflectances of pixels of objects being imaged, since these values are greatly influenced by the noise. In this paper, a new model is proposed for the determination of the noise variance of a multispectral color image acquisition system and experimental results to demonstrate its accuracy are presented. It is demonstrated that the noise variance of an actual multispectral color image acquisition system computed by the proposal agrees fairly well with the variance which minimizes the mean-square error of the recovered reflectances by the Wiener filter. As an application of the proposal, it is shown that spectral reflectances of an art painting are recovered accurately by the use of sensor responses without prior knowledge of objects being imaged and noise present in an image acquisition system.     

Optimization of sensor response functions for colorimetry ofreflective and emissive objects

This paper describes the design of color filters for a surface color measurement device. The function of the device is to return the XYZ tristimulus vector characterizing the color of the surface. The device is designed to measure emissive as well as reflective surfaces. It uses an internal set of LEDs to illuminate reflective surfaces while characterizing their color under assumed standard illuminants. In the design of the filters, we formulate a nonlinear optimization problem with the goal of minimizing error in the uniform color space CIE L*a*b*. Our optimization criteria employs a technique to retain a linear structure while approximating the true L*a*b* error. In addition, our solution is regularized to account for system noise, filter roughness, and filter implementation errors. Experimental results indicate average and worst-case device accuracy of 0.27 L*a*b* DeltaE units and 1.56 L*a*b* DeltaE units for a "system tolerance" of 0.0005.     

Natural scene-illuminant estimation using the sensor correlation

This paper describes practical algorithms and experimental results concerning illuminant classification. Specifically, we review the sensor correlation algorithm for illuminant classification and we discuss four changes that improve the algorithm's estimation accuracy and broaden its applicability. First, we space the classification illuminants evenly along the reciprocal scale of color temperature, called "mired," rather than the original color-temperature scale. This improves the perceptual uniformity of the illuminant classification set. Second, we calculate correlation values between the image color gamut and the reference illuminant gamut, rather than between the image pixels and the illuminant gamuts. This change makes the algorithm more reliable. Third, we introduce a new image scaling operation to adjust for overall intensity differences between images. Fourth, we develop the three-dimensional classification algorithms using all three-color channels and compare this with the original two algorithms from the viewpoint of accuracy and computational efficiency. The image processing algorithms incorporating these changes are evaluated using a real image database with calibrated scene illuminants     

Exploiting color for graph-based 3D point cloud denoising

A point cloud is a representation of a 3D scene as a discrete collection of geometry plus other attributes such as color, normal, transparency associated with each point. The traditional acquisition process of a 3D point cloud, e.g. using depth information acquired directly by active sensors or indirectly from multi-viewpoint images, suffers from a significant amount of noise. Hence, the problem of point cloud denoising has recently received a lot of attention. However, most existing techniques attempt to denoise only the geometry of each point, based on the geometry information of the neighboring points; there are very few works at all considering the problem of denoising the color attributes of a point cloud. In this paper, we move beyond the state of the art and we propose a novel technique employing graph-based optimization, taking advantage of the correlation between geometry and color, and using it as a powerful tool for several different tasks, i.e. color denoising, geometry denoising, and combined geometry and color denoising. The proposed method is based on the notion that the correct location of a point also depends on the color attribute and not only the geometry of the neighboring points, and the correct color also depends on the geometry of the neighbors. The proposed method constructs a suitable k-NN graph from geometry and color and applies graph-based convex optimization to obtain the denoised point cloud. Extensive simulation results on both real-world and synthetic point clouds show that the proposed denoising technique outperforms state-of-the-art methods using both subjective and objective quality metrics.     

A subspace matching color filter design methodology for a multispectral imaging system.

In this paper, we present a methodology to design filters for an imaging system to improve the accuracy of the spectral measurements for families of reflective surfaces. We derive the necessary and sufficient conditions that the sensor space of the system must obey in order to measure the spectral reflectance of the surfaces accurately. Through simulations, we show how these conditions can be applied to design filters using a set of sample spectral data acquired from extracted teeth. For this set of data, we also compare our results to those of Wolski's method, a conventional filter design method which produces filters that recover tristimulus values of surfaces accurately under several illuminants. We show that our method produces filters that capture the spectral reflectance better given the same number of measurements. The errors in predicting the color of the sample data are much lower under every test illuminant when the filters designed with our method are used.     

α-SiC/α-Si PIN异质结集成型全色色敏元件的研究

本文研究一种新型a-SiC/a-Si PIN异质结集成型全色色敏元件的制备工艺和结构,详细讨论了色敏元件的优化设计以及响应特性、暗电流等性能。实验结果表明,由于采用宽带隙的a-SiC窗口层和分离反应室的PECVD工艺,使色敏元件的灵敏度和暗电流特性得到了明显改善。     

基于线阵图像传感器的降水测量技术研究

降水现象是全球水循环和气候变化的重要研究对象.降水粒子谱资料在天气现象的自动观测、云微物理过程研究和气象雷达回波订正等领域有重要应用.基于线阵图像传感器的降水观测系统可获取降水粒子图像信息,为雨滴的微物理特性研究提供原始资料.在简述基于线阵图像传感器的降水测量系统工作原理基础上,分析了线阵降水测量关键技术及线阵数据处理相关问题,分别从光学系统参数需求、线阵传感器高速扫描和线阵数据处理等方面进行了讨论,以期线阵图像采集技术能更好地应用于降水测量.     

彩色显像管未来发展方向

随着显示器件技术的不断发展，传统显示器件正面临着新型显示器件的严峻挑战。作为传统显示器件的彩色显像管(简称CPT)如何应对这场挑战，并在激烈的市场竞争中立于不败之地，正是本文要讨论的话题。可以预言，CPT的薄型和超薄型化将是应对这一挑战的有效措施之一，也是CPT未来的发展方向。     

一种基于图像分割的几何变换映射色盲矫正方法

针对基于几何变换映射的色盲矫正方法进行色盲矫正时出现的映射计算量过高的问题,一种新型的几何变换映射色盲矫正方法被提出,这种矫正方法是基于图像分割原理的.首先研究了色盲图像的仿真方法,然后结合K-means和系统聚类算法对原始图像进行分割并计算各个区域在色盲图像下LAB颜色空间中的欧氏距离作为颜色相似性的度量,确定红绿色盲难以分辨的颜色区域.在这个区域内进行颜色映射区域的划分,这个划分主要包括根据领域内的颜色比例对空间内的几何平面进行相应变换,通过此类变换生成有利于色盲患者分辨的图案等步骤.     

SIFT-flow-based color correction for multi-view video

During the multi-view video acquisition, color variation across the views tends to be incurred due to different camera positions, orientations, and local lighting conditions. Such color variation will inevitably deteriorate the performance of the follow-up multi-view video processing, such as multi-view video coding (MVC). To address this problem, an effective color correction algorithm, called the SIFT flow-based color correction (SFCC), is proposed in this paper. First, the SIFT-flow technique is used to establish point-to-point correspondences across all the views of the multi-view video. The average color is then computed based on those identified common corresponding points and used as the reference color. By minimizing the energy of the difference yielded between the color of those identified common corresponding points in each view with respect to the reference color, the color correction matrix for each view can be obtained and used to correct its color. Experimental results have shown that the proposed SFCC algorithm is able to effectively eliminate the color variation inherited in multi-view video. By further exploiting the developed SFCC algorithm as a pre-processing for the MVC, extensive simulation results have shown that the coding efficiency of the color-corrected multi-view video can be greatly improved (on average, 0.85 dB, 1.27 dB and 1.63 dB gain for Y, U, and V components, respectively), compared with that of the original multi-view video without color correction.     

Color constancy by category correlation

Finding color representations that are stable to illuminant changes is still an open problem in computer vision. Until now, most approaches have been based on physical constraints or statistical assumptions derived from the scene, whereas very little attention has been paid to the effects that selected illuminants have on the final color image representation. The novelty of this paper is to propose perceptual constraints that are computed on the corrected images. We define the category hypothesis, which weights the set of feasible illuminants according to their ability to map the corrected image onto specific colors. Here, we choose these colors as the universal color categories related to basic linguistic terms, which have been psychophysically measured. These color categories encode natural color statistics, and their relevance across different cultures is indicated by the fact that they have received a common color name. From this category hypothesis, we propose a fast implementation that allows the sampling of a large set of illuminants. Experiments prove that our method rivals current state-of-art performance without the need for training algorithmic parameters. Additionally, the method can be used as a framework to insert top-down information from other sources, thus opening further research directions in solving for color constancy.     

基于光谱视觉响应拟合的计算机配色算法

对光谱拟合配色算法进行了讨论,并运用单常数库贝尔卡-芒克理论,导出了基于光谱视觉响应拟合的配色处方基本矩阵方程,以及配色处方修正量公式,提出了相应的计算机配色算法,建立了配色处方的修正迭代步骤。数值实验表明光谱视觉响应拟合法均衡了不同照明体下的色差,且同色异谱程度低于其他光谱拟合法。     

基于光谱视觉响应拟合的计算机配色算法

对光谱拟合配色算法进行了讨论,并运用单常数库贝尔卡-芒克理论,导出了基于光谱视觉响应拟合的配色处方基本矩阵方程,以及配色处方修正量公式,提出了相应的计算机配色算法,建立了配色处方的修正迭代步骤。数值实验表明光谱视觉响应拟合法均衡了不同照明体下的色差,且同色异谱程度低于其他光谱拟合法。     

基于ZigBee平台的多通道温度系统的开发

针对不同空间环境温度采集系统对功耗及成本的要求,设计了一种基于ZigBee平台的多通道温度采集系统。该系统硬件上以CC2430为主控芯片,选用PT100作为温度采集点的传感器,24位高精度的AD7793转换芯片实现了对温度传感器的数据信息采集。并基于ZigBee协议栈构建无线网络实现主从节点之间数据的采集与传输,软件系统基于RS232串口与ARM通信,并编程实现数据处理、存储与显示。     

Highlight‐Detection‐Based Color Correction Method for Multiview Images

In multiview imaging systems, color correction is adopted to eliminate color inconsistency between views. However, the influence of highlights on color correction has not been considered before. In this letter, a new color correction method based on highlight detection is proposed. The method is designed to treat highlight and highlight‐removal regions independently when calculating correction parameters. Finial correction is implemented with a fusion mechanism. Experimental results show that the proposed method can improve objective and subjective correction performance, while achieving better coding performance than other correction methods.     

Effect of CdSe/ZnS quantum dots on color purity and electrical properties of polyfluorene based hybrid light emitting diode

We report enhanced color purity of hybrid organic-inorganic light emitting diode based on polyfluorene-CdSe/ZnS quanum dot (QD) blend as emissive layer. Effect on structural, optical and electrical properties of different doping concentration (0–100 wt.%) of QD in polyfluorene (PFO) was studied. Photoluminescence and electroluminescence spectra confirm the β-formation of PFO by incorporation of CdSe/ZnS QD. Photoluminescence (PL) of blend film was also compared with another method based on one dimensional photonic band gap (1D-PBG) structure that has been used for color purity. In both the cases, that is, QD doped device and 1D-PBG based structures the narrowing of PL spectra was observed. But the fabrication of QD-doped device for color purity is easier than fabricating 1D-PBG structure using multilayer dielectric coating. The present study might find application for QD based color displays, where color purity is an important requirement.     

A procedure for the detection and removal of cloud shadow fromAVHRR data over land

Although the accurate detection of cloud shadow in AVHRR scenes is important for many atmospheric and terrestrial applications, relatively little work in this area has appeared in the literature. This paper presents a new multispectral algorithm for cloud shadow detection and removal in daytime AVHRR scenes over land. It uses a combination of geometric and optical constraints, derived from the pixel-by-pixel cross-track geometry of the scene and image analysis methods to detect cloud shadow. The procedure works well in tropical and midlatitude regions under varying atmospheric conditions (wet-dry) and with different types of terrain. Results also show that underdetected cloud shadow ran produce errors of 30-40% in observed reflectances for affected pixels. Moreover, radiative transfer calculations show that the effects of cloud shadow are comparable to or exceed those of aerosol contamination for affected pixels. The procedure is computationally efficient and hence could be used to produce improved weather forecast, land cover, and land analysis products. The method is not intended for use under conditions of poor solar illumination and/or poor viewing geometry