成像光谱重建及纹理色差客观评估研究
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摘要
多光谱成像是获得和显示精确颜色信息的重要技术,原因之一是多光谱图像包含了更多的光谱信息,原因之二是多光谱成像技术很好地克服了同色异谱现象。本文从光谱反射率重建这一成像系统的基本点着手,研究了反射率重建的技术,并针对成像系统聚焦模糊的现象提出了适当的模糊图像恢复技术,最后采用纹理分析方法初步研究了纹理各特性对视觉色差的影响。
维纳估计重建光谱反射率是多光谱成像中最常用的技术,本文在未知样本光谱反射率的前提下,通过自由选择适当的训练样本来求得维纳估计方法中的协方差矩阵,从而达到重建高精度反射率的目的。最后重建结果还同传统的维纳估计在不同信噪比和不同成像通道数情况下进行比较,得出在系统低信噪比或成像通道少于7的情况下,本方法求得的光谱反射率重建图像时,光谱误差和色度误差都较小。
鉴于多光谱成像中不同波段滤光片焦距的差异导致图像模糊的情况,需要采用合适的图像处理方法来恢复图像质量。本文提出对传统Unsharp Mask滤波的高频成分做加权因子修正,使图像在增强细节的同时减少噪声影响,并根据基于人眼视觉特性的质量描述参数Q值来确定最佳参数,从而实现聚焦模糊图像的恢复。且与其它方法相比,经本文所提出方法恢复后的图像在整体上具有更高的清晰度,也与理想清晰图像更为接近。
纹理这一对颜色有着重要影响的因素已成为颜色质量评价和色差估计技术中关注的焦点,本文通过实验也给出了初步的定性和定量的分析结果。定量分析中通过提取多光谱纹理图像的特征统计变量,分析其对明度方向上的视觉色差的影响,并且在分析过程中注意某些统计量之间的相关性,通过SAS软件分析减少相关统计量,以便精简最后的多变量线性回归模型。
Multispectral imaging is of great importance in color acquisition and reproduction. One reason is that multispectral images contain more spectral information; the other reason is that multispectral images can effectively eliminate the phenomenon of metamerism. This thesis presents a new method for spectral reflectance reproduction in multispectral imaging system, and introduces an image restoration method to solve the out-of-focus image blurring. We also conduct preliminary investigation on the texture effect in visual color difference evaluation.
In multispectral imaging, Wiener estimation is widely adopted for the reconstruction of spectral reflectance. We propose an improved reflectance reconstruction method by adaptively selecting training samples for the autocorrelation matrix calculation in Wiener estimation, without a prior knowledge of the spectral information of the samples being imaged. The performance of the proposed adaptive Wiener estimation and the traditional method are compared in the cases of different channel numbers and noise levels. Experimental results show that the proposed method outperforms the traditional method in terms of both spectral and colorimetric prediction errors when the imaging channel number is 7 or less.
Because of the different focus of the filters in different channels, out-of-focus blurring always occurs in the channels other than the one whose focus is appropriately adjusted, and therefore image restoration techniques are required to eliminate or reduce the blurring effect. We propose such an image restoration method by modify the strength parameter function of the traditional Unsharp Mask filter for the sake of both image sharpening and noise removal. The optimal parameters are decided according to a visual evaluation term called Q-value. Compared with other techniques, the proposed method can produce perceptually more clear images, which is also closer to the ideally focused one.
Surface texture is becoming the most interesting factor in color quality assessment and color difference evaluation areas. This thesis gives some preliminary research results through certain analysis. During the quantitative assessment process, we acquire some statistical variances of texture features through the light direction, then pays attention to the correlation between statistical variances in the hope of eliminating some variances, simplifying the final linear regression model.
维纳估计重建光谱反射率是多光谱成像中最常用的技术,本文在未知样本光谱反射率的前提下,通过自由选择适当的训练样本来求得维纳估计方法中的协方差矩阵,从而达到重建高精度反射率的目的。最后重建结果还同传统的维纳估计在不同信噪比和不同成像通道数情况下进行比较,得出在系统低信噪比或成像通道少于7的情况下,本方法求得的光谱反射率重建图像时,光谱误差和色度误差都较小。
鉴于多光谱成像中不同波段滤光片焦距的差异导致图像模糊的情况,需要采用合适的图像处理方法来恢复图像质量。本文提出对传统Unsharp Mask滤波的高频成分做加权因子修正,使图像在增强细节的同时减少噪声影响,并根据基于人眼视觉特性的质量描述参数Q值来确定最佳参数,从而实现聚焦模糊图像的恢复。且与其它方法相比,经本文所提出方法恢复后的图像在整体上具有更高的清晰度,也与理想清晰图像更为接近。
纹理这一对颜色有着重要影响的因素已成为颜色质量评价和色差估计技术中关注的焦点,本文通过实验也给出了初步的定性和定量的分析结果。定量分析中通过提取多光谱纹理图像的特征统计变量,分析其对明度方向上的视觉色差的影响,并且在分析过程中注意某些统计量之间的相关性,通过SAS软件分析减少相关统计量,以便精简最后的多变量线性回归模型。
Multispectral imaging is of great importance in color acquisition and reproduction. One reason is that multispectral images contain more spectral information; the other reason is that multispectral images can effectively eliminate the phenomenon of metamerism. This thesis presents a new method for spectral reflectance reproduction in multispectral imaging system, and introduces an image restoration method to solve the out-of-focus image blurring. We also conduct preliminary investigation on the texture effect in visual color difference evaluation.
In multispectral imaging, Wiener estimation is widely adopted for the reconstruction of spectral reflectance. We propose an improved reflectance reconstruction method by adaptively selecting training samples for the autocorrelation matrix calculation in Wiener estimation, without a prior knowledge of the spectral information of the samples being imaged. The performance of the proposed adaptive Wiener estimation and the traditional method are compared in the cases of different channel numbers and noise levels. Experimental results show that the proposed method outperforms the traditional method in terms of both spectral and colorimetric prediction errors when the imaging channel number is 7 or less.
Because of the different focus of the filters in different channels, out-of-focus blurring always occurs in the channels other than the one whose focus is appropriately adjusted, and therefore image restoration techniques are required to eliminate or reduce the blurring effect. We propose such an image restoration method by modify the strength parameter function of the traditional Unsharp Mask filter for the sake of both image sharpening and noise removal. The optimal parameters are decided according to a visual evaluation term called Q-value. Compared with other techniques, the proposed method can produce perceptually more clear images, which is also closer to the ideally focused one.
Surface texture is becoming the most interesting factor in color quality assessment and color difference evaluation areas. This thesis gives some preliminary research results through certain analysis. During the quantitative assessment process, we acquire some statistical variances of texture features through the light direction, then pays attention to the correlation between statistical variances in the hope of eliminating some variances, simplifying the final linear regression model.
引文
[1].Si-Jie Shao. "An investigation of texture effects on instrumental and visual color difference evaluation," Ph.D. dissertation(Hong Kong University Institute of Textiles and Clothing,2006)
[2].J. Y. Hardeberg. "Acquisition and reproduction of color images: colorimetric and multispectral approaches," Ph.D. dissertation(Ecole Nationale Superieure des Telecommunications, 1999)
[3].F. H. Imai "Multi-spectral image acquisition and spectral reconstruction using a trichromatic digital camera system associated with absorption filters," (Munsell Color Science Laboratory, Rochester Institute of Technology, 1998)
[4]. A. Mansouri, F. S. Marzani, J. Y. Hardeberg et al. "Optical calibration of a multispectral imaging system based on interference filters," Optical Engineering, 44(2): 027004(2005)
[5].H. Haneishi, T. Hasegawa et al. "System design for accurately estimating the spectral reflectance of art paintings," Appl. Opt. 39,6621-6632(2000)
[6].Y. Miyake, Y. Yokoyama, N. Tsumura. "Development of multiband color imaging systems for recording of art paintings," Proc. SPIE, 3648:218-225(1999)
[7].Philippe Longere, David Brainard. "Simulation of digital camera images from hyperspectral input," Vision Models and Applications to Image and Video Processing, 123-150(2001)
[8].Zhang Qiang, Guo Baolong. "Fusion of multispectral and panchromatic images based on the physical characteristics of imaging system," Acta Optica Sinica, 27(2): 243-248(2007)
[9].F. J. J. Clarke, R. McDonald, B.Rigg. "Modification to the JPC79 color-difference formula," Journal of the Society of Dyers Colourists, 100:128-132(1984)
[10]. R. McDonald, K. J. Smith. "CIE94—a new colour difference formula," Journal of the Society of Dyers Colourists, 111:376-379(1995)
[11]. M. R. Luo, G. Cui, B. Rigg. "The development of the CIE 2000 colour-difference formula: CEE2000," Color Research and Application, 26:340-350(2001)
[12]. S. S. Guan, M. R. Luo. "Investigation of parametric effects using small colour differences," Color Research and Application, 24:331-343(1999)
[13]. Publication CIE. "Parametric effects in colour-difference Evalution," CIE Central Bureau(1993)
[14]. W. K. Prat, C. E. Mancill. "Spectral estimation techniques for the spectral calibration of a color image scanner," Applied Optics, 15:73-75(1976)
[15]. Hardeberg, Schmitt, Brettel et al. "Multispectral image acquisition and simulation of illuminant changes," Color Imaging: Vision and Technology, 145-165(1999)
[16]. N. Shimano. "Recovery of spectral reflectances of objects being imaged without prior knowledge," IEEE Trans: Image Process, 15:1848-1856 (2006)
[17]. Y. Murakami, T. Obi, M. Yamaguchi et al. "Spectral reflectance estimation from multi-band image using color chart," Opt. Commun, 188:47-54 (2001)
[18]. H. L. Shen, J. H. Xin, S. J. Shao. "Improved reflectance reconstruction for multispectral imaging by combining different techniques," Opt. Express, 15: 5531-5536(2007)
[19]. Y. Murakami, T. Obi et al. "Nonlinear estimation of spectral reflectance based on Gaussian mixture distribution for color image reproduction," Appl. Opt. 41,4840-4847(2002)
[20]. H. Haneishi, T. Hasegawa, A. Hosoi et al. "System design for accurately estimating the spectral reflectance of art paintings," Appl. Opt., 39: 6621-6632 (2000)
[21]. N. Shimano. "Optimization of spectral sensitivities with Gaussian distribution functions for a color image acquisition device in the presence of noise," Opt. Eng, 45: 013201(2006)
[22].章毓晋.图像工程(上册).北京:清华大学出版社,1:28-43,271-301,305-307,2006
[23].赵荣椿,赵忠明等.数字图像处理导论.西安:西北工业大学出版社,133-160.2000
[24].Wang DC et al.Digital Image Enhancement.A Survey,GVGIP,24,1983
[25].刘政凯,瞿健雄.数字图像恢复与重建.合肥:中国科学技术出版社,1989
[26].B.R.Hunt."The application of constrained least squares estimation to image restoration by digital computer," IEEE Trans on Computer,22:805-812(1973)
[27].T.P.Costello,W.B.Mikhael."Efficient restoration of space-variant blurs from physical optics by sectioning with modified wiener filtering." Digital Signal Processing,13(1):1-22(2003)
[28].J.Barros,J.French,W.Martin et al."Indexing multispectral images for content-based retrieval," Proceedings of the 23rd AIPR Workshop on Image and Information Systems:Applications and Opportunities,1994
[29].K.N.Jabri,D.L.Wilson."Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy," Journal of the Optical Society of America,19(7):1297-1307(2002)
[30].S.H.Kim,J.P.Allebach."Optical unsharp mask for image sharpening and noise removal," Journal of Electronic Imaging,14(2):023005(2005)
[31].S.C.Matz,R.J.P.de Figueiredo."A nonlinear image contrast sharpening approach based on Munsell's scale," IEEE Transactions on Image Processing,15(4):900-909(2003)
[32].Fabrizio Russo."An image enhancement technique combining sharpening and noise reduction," IEEE Transactions on Instrumentation and Measurement,51(4):824-828(2002)
[33].B.S.Manjunath,W.Y.Ma."Texture Features for Browsing and Retrieval of Image Data," IEEE Transactions on Pattern Analysis and Machine Intelligence,18(8):837-842(1996)
[34].E.D.Montag,R.S.Berns."Lightness dependencies and the effect of texture on suprathreshold lightness tolerances," Color Research and Application,26:241-249(2000)
[35].J.H.Xin,H.L.Shen et al."Investigation of texture effect on visual color difference evaluation," Color Research and Application,30:341-347(2005)
[36].R.Huertas,M.Melgosa et al."Influence of random-dot textures on perception of suprathreshold color difference," Journal of the Optical Society of America A,23:2067-2076(2006).
[37].A.斯廷森.工程光度学与辐射学.北京:科学出版社,1-4,277-321,1984
[38].徐海松.颜色信息工程.杭州:浙江大学,15-39,40-75,77-119,122-138,2005
[39].日下秀夫.彩色图像工程.北京:科学出版社,8-50,2001
[40].D.H.Braindard."Color appearance and color difference specification," The Science of Color,second sedition,2001
[41].Haneishi,Hasegawa,Miyake et al."Design of color filters for recording art works," Proceeding of IS&T 50~(th)Annual Conference,369-372(1997)
[42].Tominaga."Multichannel vision system for estimating surface and illumination functions," Journal of the Optical Society of America,13(11):2163-2173(1996)
[43].Imai,Tsumura,Haneishi et al."Principal component analysis of skin color and its application to colorimetric color reproduction on CRT display and hardcopy," Journal of Imaging Science and Technology,40(5):422-430(1999)
[44].陈云川.视频编解码中的几个质量评价公式,2007
[45].Sharma,Truaaell."Characterization of scanner sensitivity," Proc.IS&T/SID's second Color Imaging Conference,103-107(1993)
[46].Kobus Barnard,Brian Funt."Camera characterization foe color research,"Color Research and Application,27:152-163(2002)
[47].Michael S.Brown,Peng Song,Tat-Jen Cham et al."Image pre-conditioning for out-of-focus projector blur," IEEE Computer Society Conference,Los Alamitos,California,2:1956-1963(2006)
[48].T.P.Costello,W.B.Mikhael."Efficient restoration of space-variant blurs from physical optics by sectioning with modified Wiener filtering," Digital Signal Processing,13:1-22(2003)
[49].李丙春.“基于共生矩阵的图像纹理特征提取及应用,”喀什示范学院学报,27(6),2006
[50].田艳琴,郭平,卢汉清.“基于灰度共生矩阵的多波段遥感图像纹理特征的提取,”31(12),2004
[51].M.Yamaguchi,R.Iwama,Y.Ohya."Natural color reproduction in the television system for telemedicine,"Proc.SPIE,3031:482-489(1997)
[52].Shu-xue Quan."Evaluation and optimal design of spectral sensitivities for digital color imaging," Ph.D.dissertation.(Imaging Science of the College of Science Rochester Institute of Technology,2002
[53].樊欣,邵谦谦.SAS 8.X经济统计.北京:希望电子出版社,2003
[54].Thomas Andren,Lennart Flood,Jorgen Hansen et al."Introduction to SAS,"Nationaleknomiska Institutionen Vid Goteborgs Universitet,August 1998
[55].美国SAS软件研究所上海办事处,SAS基础教程.上海:上海科学技术文献出版社,1997
[2].J. Y. Hardeberg. "Acquisition and reproduction of color images: colorimetric and multispectral approaches," Ph.D. dissertation(Ecole Nationale Superieure des Telecommunications, 1999)
[3].F. H. Imai "Multi-spectral image acquisition and spectral reconstruction using a trichromatic digital camera system associated with absorption filters," (Munsell Color Science Laboratory, Rochester Institute of Technology, 1998)
[4]. A. Mansouri, F. S. Marzani, J. Y. Hardeberg et al. "Optical calibration of a multispectral imaging system based on interference filters," Optical Engineering, 44(2): 027004(2005)
[5].H. Haneishi, T. Hasegawa et al. "System design for accurately estimating the spectral reflectance of art paintings," Appl. Opt. 39,6621-6632(2000)
[6].Y. Miyake, Y. Yokoyama, N. Tsumura. "Development of multiband color imaging systems for recording of art paintings," Proc. SPIE, 3648:218-225(1999)
[7].Philippe Longere, David Brainard. "Simulation of digital camera images from hyperspectral input," Vision Models and Applications to Image and Video Processing, 123-150(2001)
[8].Zhang Qiang, Guo Baolong. "Fusion of multispectral and panchromatic images based on the physical characteristics of imaging system," Acta Optica Sinica, 27(2): 243-248(2007)
[9].F. J. J. Clarke, R. McDonald, B.Rigg. "Modification to the JPC79 color-difference formula," Journal of the Society of Dyers Colourists, 100:128-132(1984)
[10]. R. McDonald, K. J. Smith. "CIE94—a new colour difference formula," Journal of the Society of Dyers Colourists, 111:376-379(1995)
[11]. M. R. Luo, G. Cui, B. Rigg. "The development of the CIE 2000 colour-difference formula: CEE2000," Color Research and Application, 26:340-350(2001)
[12]. S. S. Guan, M. R. Luo. "Investigation of parametric effects using small colour differences," Color Research and Application, 24:331-343(1999)
[13]. Publication CIE. "Parametric effects in colour-difference Evalution," CIE Central Bureau(1993)
[14]. W. K. Prat, C. E. Mancill. "Spectral estimation techniques for the spectral calibration of a color image scanner," Applied Optics, 15:73-75(1976)
[15]. Hardeberg, Schmitt, Brettel et al. "Multispectral image acquisition and simulation of illuminant changes," Color Imaging: Vision and Technology, 145-165(1999)
[16]. N. Shimano. "Recovery of spectral reflectances of objects being imaged without prior knowledge," IEEE Trans: Image Process, 15:1848-1856 (2006)
[17]. Y. Murakami, T. Obi, M. Yamaguchi et al. "Spectral reflectance estimation from multi-band image using color chart," Opt. Commun, 188:47-54 (2001)
[18]. H. L. Shen, J. H. Xin, S. J. Shao. "Improved reflectance reconstruction for multispectral imaging by combining different techniques," Opt. Express, 15: 5531-5536(2007)
[19]. Y. Murakami, T. Obi et al. "Nonlinear estimation of spectral reflectance based on Gaussian mixture distribution for color image reproduction," Appl. Opt. 41,4840-4847(2002)
[20]. H. Haneishi, T. Hasegawa, A. Hosoi et al. "System design for accurately estimating the spectral reflectance of art paintings," Appl. Opt., 39: 6621-6632 (2000)
[21]. N. Shimano. "Optimization of spectral sensitivities with Gaussian distribution functions for a color image acquisition device in the presence of noise," Opt. Eng, 45: 013201(2006)
[22].章毓晋.图像工程(上册).北京:清华大学出版社,1:28-43,271-301,305-307,2006
[23].赵荣椿,赵忠明等.数字图像处理导论.西安:西北工业大学出版社,133-160.2000
[24].Wang DC et al.Digital Image Enhancement.A Survey,GVGIP,24,1983
[25].刘政凯,瞿健雄.数字图像恢复与重建.合肥:中国科学技术出版社,1989
[26].B.R.Hunt."The application of constrained least squares estimation to image restoration by digital computer," IEEE Trans on Computer,22:805-812(1973)
[27].T.P.Costello,W.B.Mikhael."Efficient restoration of space-variant blurs from physical optics by sectioning with modified wiener filtering." Digital Signal Processing,13(1):1-22(2003)
[28].J.Barros,J.French,W.Martin et al."Indexing multispectral images for content-based retrieval," Proceedings of the 23rd AIPR Workshop on Image and Information Systems:Applications and Opportunities,1994
[29].K.N.Jabri,D.L.Wilson."Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy," Journal of the Optical Society of America,19(7):1297-1307(2002)
[30].S.H.Kim,J.P.Allebach."Optical unsharp mask for image sharpening and noise removal," Journal of Electronic Imaging,14(2):023005(2005)
[31].S.C.Matz,R.J.P.de Figueiredo."A nonlinear image contrast sharpening approach based on Munsell's scale," IEEE Transactions on Image Processing,15(4):900-909(2003)
[32].Fabrizio Russo."An image enhancement technique combining sharpening and noise reduction," IEEE Transactions on Instrumentation and Measurement,51(4):824-828(2002)
[33].B.S.Manjunath,W.Y.Ma."Texture Features for Browsing and Retrieval of Image Data," IEEE Transactions on Pattern Analysis and Machine Intelligence,18(8):837-842(1996)
[34].E.D.Montag,R.S.Berns."Lightness dependencies and the effect of texture on suprathreshold lightness tolerances," Color Research and Application,26:241-249(2000)
[35].J.H.Xin,H.L.Shen et al."Investigation of texture effect on visual color difference evaluation," Color Research and Application,30:341-347(2005)
[36].R.Huertas,M.Melgosa et al."Influence of random-dot textures on perception of suprathreshold color difference," Journal of the Optical Society of America A,23:2067-2076(2006).
[37].A.斯廷森.工程光度学与辐射学.北京:科学出版社,1-4,277-321,1984
[38].徐海松.颜色信息工程.杭州:浙江大学,15-39,40-75,77-119,122-138,2005
[39].日下秀夫.彩色图像工程.北京:科学出版社,8-50,2001
[40].D.H.Braindard."Color appearance and color difference specification," The Science of Color,second sedition,2001
[41].Haneishi,Hasegawa,Miyake et al."Design of color filters for recording art works," Proceeding of IS&T 50~(th)Annual Conference,369-372(1997)
[42].Tominaga."Multichannel vision system for estimating surface and illumination functions," Journal of the Optical Society of America,13(11):2163-2173(1996)
[43].Imai,Tsumura,Haneishi et al."Principal component analysis of skin color and its application to colorimetric color reproduction on CRT display and hardcopy," Journal of Imaging Science and Technology,40(5):422-430(1999)
[44].陈云川.视频编解码中的几个质量评价公式,2007
[45].Sharma,Truaaell."Characterization of scanner sensitivity," Proc.IS&T/SID's second Color Imaging Conference,103-107(1993)
[46].Kobus Barnard,Brian Funt."Camera characterization foe color research,"Color Research and Application,27:152-163(2002)
[47].Michael S.Brown,Peng Song,Tat-Jen Cham et al."Image pre-conditioning for out-of-focus projector blur," IEEE Computer Society Conference,Los Alamitos,California,2:1956-1963(2006)
[48].T.P.Costello,W.B.Mikhael."Efficient restoration of space-variant blurs from physical optics by sectioning with modified Wiener filtering," Digital Signal Processing,13:1-22(2003)
[49].李丙春.“基于共生矩阵的图像纹理特征提取及应用,”喀什示范学院学报,27(6),2006
[50].田艳琴,郭平,卢汉清.“基于灰度共生矩阵的多波段遥感图像纹理特征的提取,”31(12),2004
[51].M.Yamaguchi,R.Iwama,Y.Ohya."Natural color reproduction in the television system for telemedicine,"Proc.SPIE,3031:482-489(1997)
[52].Shu-xue Quan."Evaluation and optimal design of spectral sensitivities for digital color imaging," Ph.D.dissertation.(Imaging Science of the College of Science Rochester Institute of Technology,2002
[53].樊欣,邵谦谦.SAS 8.X经济统计.北京:希望电子出版社,2003
[54].Thomas Andren,Lennart Flood,Jorgen Hansen et al."Introduction to SAS,"Nationaleknomiska Institutionen Vid Goteborgs Universitet,August 1998
[55].美国SAS软件研究所上海办事处,SAS基础教程.上海:上海科学技术文献出版社,1997