A lightness recovery algorithm for the multispectral acquisition of frescoed environments

The multispectral acquisition of frescoes poses unsolved challenges, the main difficulty being that it is often impossible to measure the reference white signal. We introduce a new formulation of the lightness problem for images of pictorial artworks. As artists often paint the effects of light, the albedo field can contain a component that mimics an illumination field. Therefore, new insights are needed to distinguish the effects of physical illumination and painted shading. Because paint has a small dynamic range compared to light, these two signals can be distinguished using dynamic range. We describe a variational method to estimate the physical illumination component. We show our method produces estimates of the illumination intensity field for multispectral images of paintings that compare very well with the known ground truth, outperforming other state-of-the art lightness recovery algorithms. We then apply our method to a fresco for which the reference white signal had not been acquired. We propose a definition of consistency for lightness recovery algorithms, and show our method satisfies it fairly well.

[1]  E. Land,et al.  Lightness and retinex theory. , 1971, Journal of the Optical Society of America.

[2]  Berthold K. P. Horn,et al.  Determining lightness from an image , 1974, Comput. Graph. Image Process..

[3]  Andrew Blake,et al.  Boundary conditions for lightness computation in Mondrian World , 1985, Comput. Vis. Graph. Image Process..

[4]  Andrew Blake,et al.  Computing lightness , 1987, Pattern Recognit. Lett..

[5]  Mark S. Drew,et al.  Recovering Shading from Color Images , 1992, ECCV.

[6]  M. D'Zmura,et al.  Color constancy. I. Basic theory of two-stage linear recovery of spectral descriptions for lights and surfaces. , 1993, Journal of the Optical Society of America. A, Optics, image science, and vision.

[7]  Graham D. Finlayson,et al.  Color by Correlation: A Simple, Unifying Framework for Color Constancy , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[9]  Yair Weiss,et al.  Deriving intrinsic images from image sequences , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[10]  David Saunders,et al.  Ten years of art imaging research , 2002, Proc. IEEE.

[11]  Reiner Lenz,et al.  Spaces of Spectral Distributions and Their Natural Geometry , 2002, CGIV.

[12]  Michael Elad,et al.  Reduced complexity Retinex algorithm via the variational approach , 2003, J. Vis. Commun. Image Represent..

[13]  Michael Elad,et al.  A Variational Framework for Retinex , 2002, IS&T/SPIE Electronic Imaging.

[14]  Raimondo Schettini,et al.  An affordable multispectral imaging system for the digital museum , 2004, International Journal on Digital Libraries.

[15]  Claudio Oleari,et al.  Spectrophotometric Scanner for Imaging of Paintings and Other Works of Art , 2004, CGIV.

[16]  Mauro Barni,et al.  Image processing for the analysis and conservation of paintings: opportunities and challenges , 2005, IEEE Signal Process. Mag..

[17]  Edward H. Adelson,et al.  Recovering intrinsic images from a single image , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Steven D. Hordley,et al.  Scene illuminant estimation: Past, present, and future , 2006 .

[19]  Edward H. Adelson,et al.  Estimating Intrinsic Component Images using Non-Linear Regression , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[20]  Luca Poletto,et al.  A Range Camera Collecting Multi-Spectral Texture for Architecture Applications , 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

[21]  J. Mohen,et al.  Mona Lisa: Inside the Painting , 2006 .

[22]  R. Fontana,et al.  Multispectral imaging of paintings by optical scanning , 2007 .

[23]  Anna Pelagotti,et al.  Active and passive sensors for art works analysis and investigations , 2007, Electronic Imaging.

[24]  Andrea Fusiello,et al.  Recovering Intrinsic Images using an Illumination Invariant Image , 2007, 2007 IEEE International Conference on Image Processing.

[25]  Alessandro Piva,et al.  Multispectral imaging of paintings , 2008, IEEE Signal Processing Magazine.

[26]  Todd E. Zickler,et al.  Passive Reflectometry , 2008, ECCV.

[27]  Luca Poletto,et al.  Multispectral Acquisition of Large-Sized Pictorial Surfaces , 2009, EURASIP J. Image Video Process..