基于图像质量评价的显示器颜色复现技术研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
随着社会工业水平和信息化程度的不断提高,彩色显示器逐渐进入生活和生产而成为人们获得信息的主要载体。图像颜色准确复现一直是广大消费者和各显示器厂商最关心的问题之一。然而现今流行的显示器如CRT、LCD、OLED、LED显示屏等,由于显示颜色的机理不尽相同,均存在不同程度的图像跨媒体颜色复现问题。本文对显示器颜色复现流程中的若干技术进行了深入研究,提出一种基于图像质量评价的显示器颜色复现技术。
     显示器的色度特征化和色域边界描述。针对LCD、CRT显示器和LED显示屏等显示设备的色度特性化,分别给出了特征化数学模型,然后利用PR655色度计对一台LCD显示器和一台LED显示屏箱体在暗室条件下分别进行特征化实验验证,并给出相应的特性化数据和曲线拟合结果。然后提出了一种显示器色域边界快速迭代计算方法,详细介绍了算法原理并结合LED显示屏分析了算法的计算精度和速度。使用色度特征化后的点间距为3mm的LED显示屏箱体对该色域边界描述算法进行了验证。实验结果表明:11次迭代运算后,拟合色域边界已非常光滑,每条映射线上的色域边界点真实值和计算值最大色差仅为0.23。与插值类计算方法相比,最大色差值和计算速度分别降低和提高了一个数量级。该色域边界描述方法具有广泛的通用性,可用于CRT显示器和LCD显示器等可用特征矩阵表征颜色三刺激值与三原色归一化亮度关系的显示设备。
     色域映射失真图像的质量评价。本文针对色域映射失真图像,在传统图像质量评价的基础上提出了一种新的图像质量评价方法。首先将源图像和映射图像转换到CIE LAB均匀颜色空间中。对图像的明度分量,提取其相位一致性特征和边缘强度特征,对图像彩度和色相分量,根据色域映射的特点,分别提取彩度和色相分量的彩度差和色相差作为图像的另外两个特征,形成最终的质量评价公式GMSIM。使用已有的3个色域映射图像集和TID2008图像库,对GMSIM算法进行参数拟合以及算法对两种图像库主观评价结果的预测准确性实验,其中对色域映射图像集采用命中率和显著性检验来表征算法性能。实验结果显示,GMSIM算法对色域映射失真图像的主观感知预测准确性比传统的图像质量评价方法提高了约4.5%,但仍有较大的进步空间,而在TID2008图像库上的预测性能也有所提高。该图像质量评价算法可以用于设计新的色域映射算法,也可在一定程度上代替复杂费时的心理物理学主观评价实验,来验证或对比色域映射算法的效果。
     基于图像质量评价的显示器色域映射。首先介绍了“基于图像特性选择算法”类色域映射算法的各种思路并引出本文色域映射算法思路。然后详细分析了各类色域映射算法的特点并从中选用了4种算法作为基本色域映射算法。提出了一种基于GMSIM图像质量评价算法和SLIC超像素图像分割与权重图融合策略的色域映射算法FUSION-I,在每个图像分块内以图像质量评价结果为选择标准,对已有多种不同的色域映射算法进行选择综合利用。针对FUSION-I算法容易产生色块的缺点,提出了对权重图进行引导滤波的色域映射算法FUSION-II。对本文提出的两种算法和其他基本色域映射算法进行主观评价实验,结果证明本文算法在图像颜色保真效果上要优于其他算法,但在计算速度上仍有待优化。
With the improvement of industrialization and informationization level of thesociety, color display panels gradually come into life and production, and becomemain carriers from which people get information. Correct image color reproductionhas been one of the key problems that consumers and display panel manufacturerscare about. Nowadays display panels like CRT, LCD, OLED and LED display panelet al are popular, and yet because of their different color display mechanisms,cross-media image color reproduction problems exist to varying degrees. In this paper,much attention was paid on techniques in the display color reproduction workflow,and a new color reproduction algorithm based on image quality assessment wasproposed.
     Display panel color characterization and color gamut boundary description. Forthe color characterization of LCD、CRT and LED display panels, characterizationmathematical models were provided separately, and characterization experimentswere carried out for a LCD and LED display panel with a PR655colorimeter, andcorresponding characterization data and fitted curve were provided. After that, a fastand iterative gamut boundary calculation method for display panels was proposed.The method principle was introduced in detail, and the calculation accuracy and speedwas analyzed with LED display panel as an example. A color-characterized LED display panel cabinet whose pixel pitch was3mm was applied to verify the proposedgamut boundary description algorithm. Experiment result shows that the fittingboundary is very smooth after11iterations, and the maximum color differencebetween the true values and calculated values of gamut boundary points on everymapping line is only0.23. Compared with the interpolation methods, the maximumcolor difference is decreased and calculation speed is increased by an order ofmagnitude respectively. The algorithm could be extensively applied to other displaypanels like CRT and LCD whose color tri-stimulus and normalized lightness couledbe transformed by a characterization matrix。
     Quality assessment method for gamut mapping distortion images wasinvestigated. For gamut mapping distortion image, a new image quality assessmentmethod was proposed based on traditional algorithms. Firstly, both original andreproduced image are transformed into CIE LAB color space. The phase congruencyand edge strength characteristics of lightness component were extracted, and thechroma and hue difference characteristics were extracted for chroma and huecomponent, and final assessment formula named GMSIM was created based on thesefeatures. And then, being applied in3existed gamut mapping image sets and theTID2008image library, the parameters of the GMSIM algorithm were fitted, and theprediction accuracy of the algorithm was analyzed. For gamut mapping image sets, hitrate was used to indicate the algorithm performance. Experiment result shows that,compared with traditional method, the proposed GMSIM algorithm predictionaccuracy of subjective perceptions for gamut mapping distortion images wasimproved by about4.5%, although there is still much room for improvement. Theprediction performance for the TID2008image library is improved to some extent.The proposed method could be used to design new gamut mapping algorithm, and to acertain degree, it could replace the complex and time consuming subject evaluationexperiment to verify or compare the effect of different gamut mapping algorithms.
     Display gamut mapping based on image quality assessment. The ‘Choosingalgorithms based on image characteristics’ type gamut mapping algorithms wereintroduced in detail firstly, and then the supposed gamut mapping idea was given. After that, the characteristics of each sort of gamut mapping algorithms were analyzedand4ones were chosen as the basic algorithms. A gamut mapping algorithm namedFUSION-I was firstly provided based on GMSIM image quality assessment methodand SLIC superpixel image segmentation applying the weight map fusion idea, andwith image quality assessment results in each image segments as selection criteria,different sorts of gamut mapping algorithms were selected and comprehensivelyutilized. Color blocks could be generated using the FUSION-I method, and thusFUSION-II was provided based on the guided filtering of weight maps. Subjectiveevaluation experiments have been carried out for the provided2algorithms and other4basic gamut mapping ones, and experiment result shows that the proposedalgorithms were better than others in keeping image color fidelity, and yet the processspeed could be improved in the future.
引文
[1]常锋,孙志远,王瑞光,等.LED显示图像的非均匀度校正改进方法[J].光学精密工程,2011,19(4):929-937.
    [2]张鑫,王瑞光,陈宇,等.LED显示屏相机采集影像渐晕的修正[J].光学精密工程,2010,18(11):2332-2338.
    [3]岳明晶,陈宇,郑喜凤,等.大屏幕显示屏灰度等级检测技术研究[J].液晶与显示,2010,25(3):407-411.
    [4]常锋.LED显示屏灰度等级时空混合叠加调制技术研究[D]:[博士学位论文].长春:中科院长春光学精密机械与物理研究所,2011.
    [5]张鑫.全彩LED模块显示屏颜色均匀性校正研究[D]:[博士学位论文].长春:中科院长春光学精密机械与物理研究所,2011.
    [6]丁铁夫,王瑞光,严飞,宋超.LED显示屏多组并行权值时间片扫描装置:中国专利,CN200910066761.6.2011-01-19.
    [7]郑喜凤,尹柱霞,严飞,等.LED显示控制系统中SDRAM控制器的设计[J].液晶与显示,2009,24(3):423-428.
    [8] M.Stokes, M.Anderson, S.Chandrasekar, et al. A standard default color space forthe internet-sRGB [EB/OL]. http://www.w3.org/Graphics/Color/sRGB.html,1996-11-05.
    [9] IEC. IEC61966-2-1: Colour measurement and management in multimediasystems and equipment, Part2.1: Default RGB colour space-sRGB [S].1998.
    [10]International Color Consortium. ICC.1, Version4.2[S].2004.
    [11]刘瑞华.基于ICC规范的色彩管理技术研究[D]:[博士学位论文].西安:西安电子科技大学外部设备研究所,2008.
    [12]陈凌云.基于ICC规范的数字图像设备颜色管理研究[D]:[硕士学位论文].杭州:浙江大学信息学院,2007.
    [13]R.S.Berns. Methods for characterizing CRT displays [J]. Displays,1996,16(4):173-182.
    [14]R.S.Berns, R.J.Motta, M.E.Gorzynski. CRT colorimetry.[J] Part I: Theory andpractice. Color Research and Application,1993,18(5):299-314.
    [15]D.L.Post, C.S.Calhoun, An evalution of methods for producing desired colors onCRT monitors [J]. Color Research and Application,1989,14(4):172-173.
    [16]B.Kang, J.Kim, C.Yoon, et al.. WYSIWYG colour generating systemdevelopment [C]. IEEE International Conference on Computational Cyberneticsand Simulation,1997,2:1396-1400.
    [17]王勇,徐海松,许东晖,显示器颜色特性化模型比较研究[J].浙江大学学报(工学版),2006,40(6):1085-1088.
    [18]D.L.Post, C.S.Calhoun, Further evaluation of methods for producing desiredcolors on CRT monitors [J]. Color Research and Application,2000,25(2):90-104.
    [19]J.Thomas, J.Y.Hardeberg, I.Foucherot, et al. The PLVC display colorcharacterization model revisited [J]. Color Research and Application,2008,33(6):449-460.
    [20]R.I.Campeanu, J.D.McFall. Color monitor calibration based on CIE standards [C].Proceedings of the1993conference of the Centre for Advanced Studies onCollaborative research: distributed computing,1993,2:1091-1118.
    [21]Y.S.Kwak, L.W.Macdonald. Accurate prediction of colours on liquid crystaldisplays [C]. IS&T/SID Ninth Color Imaging Conference,2001:355-359.
    [22]王勇,徐海松,液晶显示器颜色特性化的S模型算法[J].中国图像图形学报,2007,12(3):491-494.
    [23]邓宏贵,李志坚,郭晟伟,等.基于LED电脉冲响应的LED显示屏像素灰度校正方法[J].发光学报,2010,31(1):145-149.
    [24] L.Svilainis. LED PWM dimming linearity investigation [J]. Displays,2008,29(3):243-249.
    [25] S.K.Ng, K.H.Loo, S.K.Ip, et al. Sequential variable bilevel driving approachsuitable for use in high-color-precision LED display panels [J]. IEEE transactionson industrial electronics,2012,59(12):4637-4645.
    [26] W.Kurdthongmee. Design and implementation of an FPGA-based multiple-colour LED display board [J]. Microprocessors and Microsystems,2005,29:327-336.
    [27] L.Svilainis. LED brightness control for video display application [J]. Displays,2008,29(5):506-511.
    [28]Arne M. Bakke, Ivar Farup and Jon Y. Hardeberg. Evaluation of algorithms forthe determination of color gamut boundaries [J]. Journal of Imaging Science andTechnology,2010,54(5):50502-1-50502-11.
    [29]黄庆梅,赵达尊.基于Zernike多项式表示色域边界的色域映射[J].光学技术,2003,29(2):168-171.
    [30]P.G.Herzog. Further development of the analytical color gamut representation [J].SPIE,1998,3300:118-128.
    [31]息丽丽,王义峰,刘瑞华,等.基于B样条色域描述的颜色匹配[J].计算机工程,2008,33(01):210-214.
    [32]Jan Morovic, M. Ronnier Luo. Calculating Medium and Image GamutBoundaries for Gamut Mapping [J]. Color Research and Application,2000,25(6):394-401.
    [33]CIE Technical Committee8-03. Guidelines for the evaluation of gamut mappingalgorithms[R]. CIE,2004.
    [34]T.J.Cholewo, S.Love. Gamut boundary determination using alpha-shapes [C].Proceedings of7th IS&T/SID Color Imaging Conference,1999,200-204.
    [35]C.Barber,D.Dobkin,H.Huhdanpaa. The quickhull algorithm for convex hulls [J].ACM Transactions on Mathematical Software,1996,22(4):469-483.
    [36]徐艳芳,刘文耀.数字影像输出设备色域边界的插值计算方法[J].光学精密工程,2006,14(02):262-265.
    [37]王义峰,刘瑞华,曾平.测量与样条插值相结合的打印机色域提取[J].华中科技大学学报(自然科学版),2007,35(7):15-17.
    [38]蒋刚毅,黄大江,王旭,等.图像质量评价方法研究进展[J].电子与信息学报,2010,32(1):221-226.
    [39]Lin Zhang, Lei Zhang, Xuanqin Mou, et al. A comprehensive evaluation of fullreference image quality assessment algorithms [C]. IEEE InternationalConference on Image Processing,2012,1477-1480.
    [40]高新波,路文.视觉信息质量评价方法[M].西安:西安电子科技大学出版社,2010.1-10.
    [41]W. Lin, C.Kuo. Perceptual visual quality metrics: A survey [J]. Journal of VisualCommunication and Image Representation,2011,22(4):297-312.
    [42]X.Zhang, B.Wandell. A spatial extension to CIE LAB for digital color imagereproduction [J]. Journal of the Society for Information Display,1997,5(1):61-63.
    [43]G.M.Johnson, M.Fairchild. A top down description of S-CIELAB andCIEDE2000[J]. Color Research and Application,2003,28(6):425-435.
    [44]Zhou Wang, Alan Contrad Bovik, Hamid Rahim Sheikh, et al. Image qualityassessment: From error visibility to structural similarity [J]. IEEE Transactions onImage Processing,2004,13(4):600-612.
    [45]Hamid Rahim Sheikh, Alan Contrad Bovik.Image information and visual quality[J]. IEEE Transactions on Image Processing,2006,15(2):430-444.
    [46]Lin Zhang, Lei Zhang, Xuanqin Mou, et al. FSIM: A feature similarity index forimage quality assessment [J]. IEEE Transactions on Image Processing,2011,20(8):2378-2386.
    [47]Damon M.Chandler, Sheila S.Hemami. VSNR: A wavelet-based visualsignal-to-noise ratio for natural images [J]. IEEE Transactions on ImageProcessing,2007,16(9):2284-2298.
    [48]Jan Morovic. To develop a universal gamut mapping algorithm [D]. UnitedKingdom: University of Derby,1998.
    [49]Jan Morovic, M. Ronnier Luo. The fundamentals of gamut mapping: A survey [J].Journal of Imaging Science and Technology,2001,45(3):283-290.
    [50]Jan Morovic. Color gmut mapping [M]. England:Jon Wiley&Sons Ltd,2008.
    [51]陈谊,姚海根,冷高亮.彩色复制中色域映射算法研究现状[J].仪器仪表学报,2006,27(6):789-791.
    [52]黄庆梅,赵达尊.彩色复制中的色域映射[J].照明工程学报,2002,13(1):19-26.
    [53]张显斗.数字图像颜色复现理论与方法研究[D]:[博士学位论文].杭州:浙江大学信息学部,2010.
    [54]CIE. CIE156. Guidelines for the evaluation of Gamut Mapping Algorithms [S],2004.
    [55]杨露,刘真,吴明光.与图像相关的色域映射算法研究[J].中国印刷与包装研究,2013,5(3):11-17.
    [56]Golan. Novel workflow for image-guided gamut mapping [J]. Journal ofElectronic Imaging,2008,17(3):1-11.
    [57]Z.Baranczuk. Image-Individualized Gamut Mapping Algorithms [J]. Journal ofImaging and Technology,2010,54(3):030201-030201-7.
    [58]王义峰,罗雪梅,曾平.基于视觉评价模型的色域匹配算法[J].西安电子科技大学学报(自然科学版),2008,35(5):878-882.
    [59]G.J.Braun. Gamut mapping for pictorial images [J]. TAGA Proceedings,1999,645-660.
    [60]H.Chen, H.Kotera. Three-dimensional gamut mapping method based on theconcept of image dependence [J]. Jornal of Imaging Science and Technology,2002,46(1):44-52.
    [61]R.Balasubramanian, R.deQueiroz, R.Eschbach, et al. Gamut mapping to preservespatial luminance variations [C]. Proceeding of IS&T and SID’s8thColorImaging Conference: Color Science and Engineering,2000,122-126.
    [62]P.Zolliker, K.Simon. Retaining local Image information in gamut mappingalgorithms [J]. IEEE Transactions On Image Processing,2007,16(3):664-672.
    [63]N.Bonnier, F.Schmitt, M.Hull. Spatial and color adaptive gamut mapping: amathematical framework and two new algorithms [C]. Proceedings of the15thIS&T/SID Color Imaging Conference,2007,267-272.
    [64]J.Morovic, Y.Wang. A multi-resolution, full-colour spatial gamut mappingalgorithm [C].11th IST/SID Color Imaging Conference,2003,282-287.
    [65]Farup, C.Gatta, A.Rizzi. Amultiscale framework for spatial gamut mapping [J].IEEE Transactions on Image Processing,2007,16(10):2423-2435.
    [66]S.Nakauchi, S.Hatanaka, S.Usui. Color gamut mapping based on a perceptualimage difference measure [J]. Color Research and Application,1999,24(4):280-291.
    [67]J.J.McCann. Color gamut mapping using spatial comparisons [J]. SPIE,2001,4300:126-130.
    [68]R.Kimmel, D.Shaked, M.Elad. Space-dependent color gamut mapping: avariational approach [J]. IEEE Transactions on Image Processing,2005,14(6):796-803.
    [69]Nikolay Ponomarenko, Vladimir Lukin, Alexander Zelensky, et al. TID2008-Adatabase for evaluation of full-reference visual quality assessment metrics[J].Advances of Modern Radioelectronis,2009,10:30-45.
    [70]胡威捷,汤顺青,朱正芳.现代颜色技术原理及应用[M].北京:北京理工大学出版社,2007.1-3.
    [71]N.Ohta, A.Robertson. Colorimetry-Fundamentals and Applications [M].England:John Wiley&Sons Ltd,2005.10-50.
    [72]ITU-R. Rec.BT.500-11.Methodology for the subjective assessment of the qualityof television pictures [S],2002.
    [73]丁柏秀.基于多项式回归逼近的LED显示色域变换技术研究[D]:[博士学位论文].长春:中科院长春光学精密机械与物理研究所,2013.
    [74]陈强,陈贺新,李文娟.基于3维矩阵变化的彩色图像质量评价方法研究[J].中国图像图形学报,2006,11(11):1732-1735.
    [75]陈勇,李愿,吕霞付,等.视觉感知的彩色图像质量积极评价[J].光学精密工程,2013,21(3):742-750.
    [76]高昆,程新满,吕丽丽,等.结合人眼视觉综合感知差与r_g色域峰值偏差的彩色图像客观评价方法[J].北京理工大学学报,2012,32(3):286-290.
    [77]黄小乔,石俊生,杨健,等.基于色差的均方误差与峰值信噪比评价彩色图像质量研究[J].光子学报,2007,36增刊:295-298.
    [78]黄小乔,石俊生,姚军财,等.一种基于S-CIELAB的图像质量评价模型[J].云南师范大学学报,2006,26(5):48-51.
    [79]王宇庆,刘维亚,王勇.基于四元数的彩色图像质量评价方法[J].中北大学学报(自然科学版),2010,31(1):59-64.
    [80]王宇庆,朱明.评价彩色图像质量的四元数矩阵最大奇异值方法[J].光学精密工程,2013,21(2):469-478.
    [81]武海丽,黄庆梅,苑馨方,等.基于S-CIELAB和iCAM模型的图像颜色质量评价方法的实验研究[J].光学学报,2010,30(12):3447-3453.
    [82]M.Concetta Morrone, John Ross, David C.Burr, et al. Mach bands are phasedependent [J]. Nature,1986,324(6049):250-253.
    [83]Peter Kovesi. Image features from phase congruency [J]. Videre: A Journal ofComputer Vision Research,1999,1(3):1-26.
    [84]卢振泰,冯衍秋,冯前进,等.基于主相位一致性的医学图像配准[J].电子学报,2008,36(10):1974-1978.
    [85]汪剑鸣,窦汝振,王中伟,等.相位一致性的理解及两种新的相位一致性模型[J].计算机应用研究,2010,27(5):1948-1951.
    [86]王正友,李振兴,林维斯,等.结合HVS和相似特征的图像质量评估方法[J].仪器仪表学报,2012,33(7):1606-1612.
    [87]苑玮琦,范永刚,柯丽.相位一致性和对数Gabor滤波器相结合的掌纹识别方法[J].光学学报,2010,30(1):147-152.
    [88]Anmin Liu, Weisi Lin, Manish Narwaria. Image quality assessment based ongradient similarity [J]. IEEE Transactions on Image Processing,2012,21(4):919-932.
    [89]Pietro Persona, Jitendra Malik. Scale-space and edge detection using anisotropicdiffusion [R].Department of EECS Technical Report, University of California,1988.
    [90]Xuande Zhang, Xiangchu Feng, Weiwei Wang, et al. Edge strength similarity forimage quality assessment [J]. IEEE Signal Processing Letters,2013,20(4):319-322
    [91]M.Scheller Lichtenauer, P.Zoliker, I.Lissner, et al. Learning image similaritymeasures from choice data [C]. European Conference on Color in Graphics,Imaging, and Vision,2012,24-30.
    [92]L.Brown, X.Li. Confidence intervals for two sample binomial distribution [J].Journal of Statistical Planning and Inference,2005,130(2005):359-375.
    [93]J.Shi, J.Malik. Normalized cuts and image segmentation [C]. IEEE ComputerSociety Conference on Computer Vision and Pattern Recognition,1997:731-737.
    [94]Xiaofeng Ren, Jitendra Malik. Learning a classification model for segmentation[C]. IEEE International Conference on Computer Vision,2003,1:10-17.
    [95]Radhakrishna Achanta, Appu Shaji, Kevin Smith, et al. SLIC Superpixels [R].EPFL Technical Report,2010.
    [96]Radhakrishna Achanta, Appu Shaji, Kevin Smith, et al. SLIC Superpixelscompared to state-of-the-art superpixel methods [J]. IEEE Transactions on PatternAnalysis and Machine Intelligence,2012,34(11):2274-2282.
    [97]Radhakrishna Achanta, Appu Shaji, Kevin Smith, et al. SLIC Superpixelscompared to state-of-the-art superpixel methods [J]. IEEE Transactions on PatternAnalysis and Machine Intelligence,2012,34(11):2274-2282.
    [98]Vedaldi, B.Fulkerson. VLFeat: An open and portable library of computer visionalgorithms [EB/OL]. http://www.vlfeat.prg/,2008.
    [99]R.C.Gonzalez, R.E.Woods. Digital image processing [M]. USA: Prentice Hall,2002.
    [100] C.Tomasi, R.Manduchi. Bilateral filtering for gray and color images [C].IEEE International Conference on Computer Vision,1998,839-846
    [101] K.He, J.Sun, X.Tang. Guided image filtering [C]. European Conference onComputer Vision,2010,1-14
    [102] K.He, J.Sun, X.Tang. Guided image filtering [J]. IEEE Transactions onPattern Analysis and Machine Intelligence,2013,35(6):1397-1409.
    [103] L.L.Thurstone.A law of comparative judgement [J]. Psychological Review,1994,101(2):266-270.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700