一种基于LMS加权的残差补偿光谱降维模型研究

目的在PCA算法的基础上提出一种基于LMS锥响应加权的残差补偿光谱降维模型。方法介绍以LMS为加权函数对源光谱加权以及用残差光谱对模型补偿的基本框架。以Munsell色卡作为训练样本,以多光谱图像和SG色卡为检测样本,用文中算法与主成分分析算法分别对其进行降维、重构。结果在不同维数下,采用文中算法重构都具有较高的色度精度,该算法有效提高了主成分分析算法的色度精度,且在变光源情况下仍具有较高的色度稳定性。结论该降维算法采用LMS加权并对残差光谱补偿是一种精度较高的光谱降维模型。     

面向颜色再现的光谱降维方法研究

目的为了解决颜色信息光谱反射率的高维数给颜色再现过程带来的诸多问题。方法利用主流的光谱降维方法(主成分分析,Lab PQR,WSPCA,WSPCAplus),实现利于颜色再现的光谱信息筛选,从光谱精度、色度精度及变光源色差稳定性等3个方面评价这些降维方法。结果实验证明,主成分分析(PCA)法的光谱精度最高,光谱误差只有0.0076,但是在色度精度及变光源色差稳定性方面表现不好;Lab PQR法在光谱精度和色度精度间达到了很好的平衡,但是当变换光源时,其色差稳定性较差;WSPCA法去除了光源的影响,其变光源后色差变化不大,并且同时兼顾了色度精度,但以牺牲光谱精度为代价,WSPCAplus在其基础上将光谱精度提高为0.0081。结论研究结果对颜色再现过程中降维方法的选择具有一定的指导作用。     

不同算法模型对光谱重构精度的影响

目的研究光谱颜色复制中原稿图像的光谱信息,并对目标色的光谱反射率进行重构,探究影响重构光谱精度的因素。方法通过选取Munsell Color Matt(1269色块)和Color Checker Classic(24色块)2种色卡作为光谱反射率数据样本,建立不同的主成分分析线性重构模型,选取不同的基向量个数分别重构光谱,并对其精度进行评价,取Classic色卡模拟多光谱图像中重建光谱反射率的目标色,研究比较光谱重构模型和基向量数目对重构精度的影响。结果实验表明,降维模型1最终恢复的数据在RMSE,GFC和色差上均优于模型2,随着基向量数目的增加,2种降维模型差距在减小,当基向量数目达到13以后,2种模型基本没差异。结论文中提到光谱重建模型1和7个基向量是重构光谱图像的最佳方案。     

基于 BP 神经网络的多基色打印机光谱特性化

目的实现多基色打印机的光谱特性化。方法结合光谱降维和光谱重构方法建立了多基色打印机光谱特性化BP神经网络模型,并提出了基于人眼视觉特性加权的目标函数。结果在基于BP神经网络的多基色打印机光谱特性化中,当目标函数未进行人眼视觉特性加权时,光谱精度和色度精度分别为0.0285和2.8614,当采用人眼视觉特性加权目标函数后,光谱精度和色度精度分别为0.0166和1.2247。结论在基于BP神经网络的多基色打印机光谱特性化中,使用基于人眼视觉特性加权的目标函数可兼顾光谱与色度2个因素,其光谱特性化效果更优。     

基于GA-BP神经网络的彩色扫描仪光谱特征化

为了实现彩色扫描仪的光谱特征化,采用一种GA修正的BP神经网络与PCA相结合的方法对其进行研究。首先,通过主成分分析,对训练样本的光谱反射率进行降维,以RGB信号和降维后的光谱数据作为输入、输出变量进行GA-BP神经网络的建模,对任意RGB信号都可以通过模型得到其低维光谱信号;再通过主成分分析重构光谱反射率,由此实现RGB信号对光谱反射率的重构,即实现扫描仪的光谱特征化。实验结果表明,GA的优化有效地改善了BP神经网络的极值问题,提高了模型的预测精度,PCA在不影响模型精度的同时提高了模型的效率。由此说明,所提出的模型能够满足扫描仪光谱特征化的需求。     

同色异谱黑在光谱降维中的应用研究

目的研究同色异谱黑在光谱降维中的应用。方法基于同色异谱黑光谱特性提出MBPCA光谱降维法。该方法将颜色光谱分解为基本光谱和同色异谱黑光谱,基本光谱的基向量由原始光谱通过PCA法得到的前3个基向量构成,原始光谱与基本光谱之间的残余光谱作为同色异谱黑光谱,其基向量由残余光谱通过PCA法推导。结果当降维光源与实际光照光源一致时,只要基向量数目超过3个,其低维模型的色度精度皆为0,当用6个基向量重构光谱时,在4种标准光源下的平均色差接近于1。结论 MBPCA法与PCA法相比,其光谱重构精度与PCA法接近,色度精度比PCA法有明显提高,其六维模型能有效满足光谱颜色复制的需要。     

面向高保真再现的多光谱图像降维方法

目的研究满足面向高保真再现要求的多光谱图像降维方法。方法基于二进制小波对信号的分解与人类的视觉特性相匹配,以及非负主成分分析法可较好地保证降维的光谱精度,提出采用基于离散二进制小波变化与非负主成分分析法的综合降维方法,并基于多光谱图像高保真再现的光谱精度、色度精度与变光源色差稳定性的要求,提出采用CIELAB的标准色差ab?E、光谱保真度和平均梯度等3个指标来评价降维效果。结果经过多光谱图像的测试实验,基于离散小波变换和非负主成分分析法的综合降维方法相对于其他3种方法,其光谱精度、色度精度和图像清晰度保持良好。结论该方法较好地实现了多光谱图像的高保真再现问题,并且为颜色视觉的认知过程提供了新的理论解释。     

基于视觉特性的LCD显示器光谱特征化方法

目的实现LCD显示器RGB颜色空间到颜色光谱高效的特征化。方法利用主成分分析法对光谱数据进行降维处理以及借助RBF神经网络研究输入变量数据范围、视觉加权函数和颜色数量对特征化模型的精度影响。结果主成分个数为6时可以很好地保留光谱原来的信息;输入变量范围为0到2.55,CIE1931视觉函数作为加权函数,颜色数量为364时特征化精度高,客观验证99个颜色转换的平均色差为0.36,最大色差为1.59,总样本的平均色差为0.17。结论输入变量数据范围对模型影响最大,视觉加权函数和颜色数量次之,因此在特征化时要考虑输入变量范围、视觉加权函数和颜色数量,这样可以提高模型的精度。文中提出的模型是一种精度较高的特征化模型,具有一定实际应用价值。     

修改LMS加权特性的PCA空间内光谱色域映射模型

目的针对跨媒体光谱颜色复制中不同颜色媒介光谱色域不一致的问题,在LMS-PCA光谱空间下构建一种修改LMS加权特性的PCA空间内光谱色域映射模型。方法利用调整后的修改LMS加权函数对高维光谱数据进行加权,采用主成分分析法提取其加权光谱的前3个主成分,用以构建LMS-PCA光谱链接空间。在LMS-PCA空间内引入分区成熟SMGBD算法描述设备的光谱色域,对超出设备光谱色域的图像颜色点进行LSLINce Lmax色域压缩以映射到设备光谱域内,LSLINce Lmax色域压缩基于传统LSLIN算法优化得到。结果新模型相比于利用其他色域映射方向的光谱色域映射模型,以及普通加权视觉特性的PCA空间内光谱域映射模型,拥有更高的光谱精度和色度精度,且在变观察环境下具有稳定的色差精度。结论修改LMS加权特性的PCA空间内色域映射模型能够基本解决变观察环境下,不同颜色媒介光谱色域不一致的问题,具有较好的实用性。     

基于颜色属性的光谱重建训练样本正交优化

选择具有代表性的颜色作为光谱重建的训练样本可以有效减少样本冗余,提高光谱重建精度。采用正交试验方法,基于色相、明度和饱和度在Munsell颜色集中选择具有代表性的颜色样本,并分析颜色三属性对光谱重建精度的影响。结果表明,采用主成分分析(PCA)法重建得到的反射率与原反射率的平均均方差(RMS)最大可达0.120 4,而采用违逆(PSE)法和R矩阵(R-matrix)法重建得到的平均RMS相对较小。三属性的优先级别R极差分析中,明度明显大于色相和饱和度。颜色三属性对P C A法的影响大于对PSE法和R-matrix法。明度对光谱重建精度的影响较大,而色相和饱和度对光谱重建精度的影响相对较小。     

Weighted compression of spectral color information

Spectral color information is used nowadays in many different applications. Accurate spectral images are usually very large files, but a proper compression method can reduce needed storage space remarkably with a minimum loss of information. In this paper we introduce a principal component analysis (PCA) -based compression method of spectral color information. In this approach spectral data is weighted with a proper weight function before forming the correlation matrix and calculating the eigenvector basis. First we give a general framework for how to use weight functions in compression of relevant color information. Then we compare the weighted compression method with the traditional PCA compression method by compressing and reconstructing the Munsell data set consisting of 1,269 reflectance spectra and the Pantone data set consisting of 922 reflectance spectra. Two different weight functions are proposed and tested. We show that weighting clearly improves retention of color information in the PCA-based compression process.     

Improvement of color reproduction in color digital holography by using spectral estimation technique

We propose a color digital holography by using spectral estimation technique to improve the color reproduction of objects. In conventional color digital holography, there is insufficient spectral information in holograms, and the color of the reconstructed images depend on only reflectances at three discrete wavelengths used in the recording of holograms. Therefore the color-composite image of the three reconstructed images is not accurate in color reproduction. However, in our proposed method, the spectral estimation technique was applied, which has been reported in multispectral imaging. According to the spectral estimation technique, the continuous spectrum of object can be estimated and the color reproduction is improved. The effectiveness of the proposed method was confirmed by a numerical simulation and an experiment, and, in the results, the average color differences are decreased from 35.81 to 7.88 and from 43.60 to 25.28, respectively.     

CCD传感器噪声对遥感影像无损压缩的影响

为分析CCD传感器噪声对遥感影像无损压缩的影响,选取ISO/IEC标准图像和UK-DMC多光谱影像作为测试图像,根据CCD传感器噪声模型,在测试图像上添加CCD传感器模拟噪声,采用JPEG2000-Lossless无损压缩算法对不同污染程度的噪声图像进行压缩处理,并对不同污染程度的噪声影像无损压缩比进行比较分析.而后,在多光谱遥感影像上添加模拟的混合噪声,分析CCD噪声对星地间数据传输效率的影响.实验结果表明,CCD传感器噪声对所获取影像的污染会降低遥感影像的无损压缩比和星地间数据传输效率,以泊松噪声为模型的散粒噪声与读出噪声对影像无损压缩的影响最大,以高斯噪声为模型的热噪声与暗电流噪声的影响次之,由于CCD器件工艺问题引发的脉冲噪声对无损压缩的影响最小.     

Maximum a posteriori estimation of spectral reflectance from color image and multipoint spectral measurements

Accurate color image reproduction under arbitrary illumination can be realized if the spectral reflectance functions in a scene are obtained. Although multispectral imaging is one of the promising methods to obtain the reflectance of a scene, it is expected to reduce the number of color channels without significant loss of accuracy. This paper presents what we believe to be a new method for estimating spectral reflectance functions from color image and multipoint spectral measurements based on maximum a posteriori (MAP) estimation. Multipoint spectral measurements are utilized as auxiliary information to improve the accuracy of spectral reflectance estimated from image data. Through simulations, it is confirmed that the proposed method improves the estimation accuracy, particularly when a scene includes subjects that belong to various categories.     

Recovering fluorescent spectra with an RGB digital camera and color filters using different matrix factorizations

The aim of a multispectral system is to recover a spectral function at each image pixel, but when a scene is digitally imaged under a light of unknown spectral power distribution (SPD), the image pixels give incomplete information about the spectral reflectances of objects in the scene. We have analyzed how accurately the spectra of artificial fluorescent light sources can be recovered with a digital CCD camera. The red-green-blue (RGB) sensor outputs are modified by the use of successive cutoff color filters. Four algorithms for simplifying the spectra datasets are used: nonnegative matrix factorization (NMF), independent component analysis (ICA), a direct pseudoinverse method, and principal component analysis (PCA). The algorithms are tested using both simulated data and data from a real RGB digital camera. The methods are compared in terms of the minimum rank of factorization and the number of sensors required to derive acceptable spectral and colorimetric SPD estimations; the PCA results are also given for the sake of comparison. The results show that all the algorithms surpass the PCA when a reduced number of sensors is used. The experimental results suggest a significant loss of quality when more than one color filter is used, which agrees with the previous results for reflectances. Nevertheless, an RGB digital camera with or without a prefilter is found to provide good spectral and colorimetric recovery of indoor fluorescent lighting and can be used for color correction without the need of a telespectroradiometer.