Imaging Spectroscopy for Scene Analysis

This book presents a detailed analysis of spectral imaging, describing how it can be used for the purposes of material identification, object recognition and scene understanding. The opportunities and challenges of combining spatial and spectral information are explored in depth, as are a wide range of applications. Features: discusses spectral image acquisition by hyperspectral cameras, and the process of spectral image formation; examines models of surface reflectance, the recovery of photometric invariants, and the estimation of the illuminant power spectrum from spectral imagery; describes spectrum representations for the interpolation of reflectance and radiance values, and the classification of spectra; reviews the use of imaging spectroscopy for material identification; explores the recovery of reflection geometry from image reflectance; investigates spectro-polarimetric imagery, and the recovery of object shape and material properties using polarimetric images captured from a single view.

[1]  Matthew A. Brown,et al.  Learning Local Image Descriptors , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Nuno Vasconcelos,et al.  On the efficient evaluation of probabilistic similarity functions for image retrieval , 2004, IEEE Transactions on Information Theory.

[3]  A. B. Lefkoff,et al.  Expert system-based mineral mapping in northern death valley, California/Nevada, using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) , 1993 .

[4]  Stefan Rahmann,et al.  Polarization images: a geometric interpretation for shape analysis , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[5]  H. Jeffreys An invariant form for the prior probability in estimation problems , 1946, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[6]  L. Piegl,et al.  The NURBS Book , 1995, Monographs in Visual Communications.

[7]  Guy Godin,et al.  Separation of diffuse and specular components of surface reflection by use of polarization and statistical analysis of images , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Cong Phuoc Huynh,et al.  Shape and refractive index recovery from single-view polarisation images , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  David J. Kriegman,et al.  The Bas-Relief Ambiguity , 2004, International Journal of Computer Vision.

[10]  J. Koenderink The structure of images , 2004, Biological Cybernetics.

[11]  Robert Tibshirani,et al.  Classification by Pairwise Coupling , 1997, NIPS.

[12]  Grahame B. Smith The Recovery of Surface Orientation from Image Irradiance , 1982 .

[13]  K. Torrance,et al.  Theory for off-specular reflection from roughened surfaces , 1967 .

[14]  Sellmeier Zur Erklärung der abnormen Farbenfolge im Spectrum einiger Substanzen , 1871 .

[15]  L. Mandel,et al.  Optical Coherence and Quantum Optics , 1995 .

[16]  A. Householder,et al.  Discussion of a set of points in terms of their mutual distances , 1938 .

[17]  Demetri Terzopoulos,et al.  Multilevel computational processes for visual surface reconstruction , 1983, Comput. Vis. Graph. Image Process..

[18]  K. F. Riley,et al.  Mathematical Methods for Physics and Engineering , 1998 .

[19]  Rui J. P. de Figueiredo,et al.  A Theory of Photometric Stereo for a Class of Diffuse Non-Lambertian Surfaces , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Mireille Guillaume,et al.  Minimum Dispersion Constrained Nonnegative Matrix Factorization to Unmix Hyperspectral Data , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[21]  Carle M. Pieters,et al.  Mathematical Deconvolution of Mineral Absorption Bands , 1989 .

[22]  B. Scholkopf,et al.  Fisher discriminant analysis with kernels , 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

[23]  Sen Jia,et al.  Constrained Nonnegative Matrix Factorization for Hyperspectral Unmixing , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Rama Chellappa,et al.  Estimation of Illuminant Direction, Albedo, and Shape from Shading , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  K. Ikeuchi,et al.  Determining surface orientations of transparent objects based on polarization degrees in visible and infrared wavelengths. , 2002, Journal of the Optical Society of America. A, Optics, image science, and vision.

[26]  Wei Zhou,et al.  Estimation of Illuminant Direction and Intensity of Multiple Light Sources , 2002, ECCV.

[27]  Stanley Osher,et al.  L1 unmixing and its application to hyperspectral image enhancement , 2009, Defense + Commercial Sensing.

[28]  D. B. Judd,et al.  Spectral Distribution of Typical Daylight as a Function of Correlated Color Temperature , 1964 .

[29]  Azriel Rosenfeld,et al.  Improved Methods of Estimating Shape from Shading Using the Light Source Coordinate System , 1985, Artif. Intell..

[30]  Edwin R. Hancock,et al.  Shape from Periodic Texture Using the Eigenvectors of Local Affine Distortion , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Mario Winter,et al.  N-FINDR: an algorithm for fast autonomous spectral end-member determination in hyperspectral data , 1999, Optics & Photonics.

[32]  John Platt,et al.  Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods , 1999 .

[33]  Max Born,et al.  Principles of optics - electromagnetic theory of propagation, interference and diffraction of light (7. ed.) , 1999 .

[34]  Ronald L. Graham,et al.  An Efficient Algorithm for Determining the Convex Hull of a Finite Planar Set , 1972, Inf. Process. Lett..

[35]  Daphna Weinshall,et al.  The shape of shading , 1990 .

[36]  Katsushi Ikeuchi,et al.  Transparent surface modeling from a pair of polarization images , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[37]  Olivier D. Faugeras,et al.  "Perspective shape from shading" and viscosity solutions , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[38]  M. Born Principles of Optics : Electromagnetic theory of propagation , 1970 .

[39]  Steven A. Shafer,et al.  Anatomy of a color histogram , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[40]  Victoria Stodden,et al.  When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts? , 2003, NIPS.

[41]  L. B. Wolff Diffuse-reflectance model for smooth dielectric surfaces , 1994 .

[42]  Paul D. Gader,et al.  Hyperspectral Band Selection and Endmember Detection Using Sparsity Promoting Priors , 2008, IEEE Geoscience and Remote Sensing Letters.

[43]  Maurice D. Craig,et al.  Minimum-volume transforms for remotely sensed data , 1994, IEEE Trans. Geosci. Remote. Sens..

[44]  M. S. Alencar,et al.  A relation between the Renyi distance of order /spl alpha/ and the variational distance , 1998, ITS'98 Proceedings. SBT/IEEE International Telecommunications Symposium (Cat. No.98EX202).

[45]  Trevor Darrell,et al.  The Pyramid Match Kernel: Efficient Learning with Sets of Features , 2007, J. Mach. Learn. Res..

[46]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[47]  Jan-Olof Eklundh,et al.  Automatic estimation of the projected light source direction , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[48]  Shree K. Nayar,et al.  Generalized Assorted Pixel Camera: Postcapture Control of Resolution, Dynamic Range, and Spectrum , 2010, IEEE Transactions on Image Processing.

[49]  Yee-Hong Yang,et al.  Multiple Illuminant Direction Detection with Application to Image Synthesis , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[50]  Hairong Qi,et al.  Endmember Extraction From Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[51]  Katsushi Ikeuchi,et al.  Measurement of surface orientations of transparent objects using polarization in highlight , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[52]  H. Sebastian Seung,et al.  Learning the parts of objects by non-negative matrix factorization , 1999, Nature.

[53]  Graham D Finlayson,et al.  Analytic solution for separating spectra into illumination and surface reflectance components. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[54]  Thomas M. Strat,et al.  A Numerical Method for Shape-From-Shading from a Single Image. , 1979 .

[55]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[56]  D. Voelz,et al.  Polarization-based index of refraction and reflection angle estimation for remote sensing applications. , 2007, Applied optics.

[57]  Shree K. Nayar,et al.  Reflectance based object recognition , 1996, International Journal of Computer Vision.

[58]  Bo-Cai Gao,et al.  Development of a line-by-line-based atmosphere removal algorithm for airborne and spaceborne imaging spectrometers , 1997, Optics & Photonics.

[59]  Shree K. Nayar,et al.  Eyes for relighting , 2004, SIGGRAPH 2004.

[60]  Katsushi Ikeuchi,et al.  Illumination distribution from shadows , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[61]  Terrance E. Boult,et al.  Constraining Object Features Using a Polarization Reflectance Model , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[62]  Jing Wang,et al.  Applications of Independent Component Analysis in Endmember Extraction and Abundance Quantification for Hyperspectral Imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[63]  Katsushi Ikeuchi,et al.  Temporal-color space analysis of reflection , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[64]  David R. Thompson,et al.  Sparse superpixel unmixing for exploratory analysis of CRISM hyperspectral images , 2009, 2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing.

[65]  Hua Chen,et al.  Polarization Phase-Based Method For Material Classification In Computer Vision , 1998, International Journal of Computer Vision.

[66]  Terrance E. Boult,et al.  Polarization/radiometric based material classification , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[67]  Andrei Doncescu,et al.  Feature Selection for Fault Diagnosis Using Fuzzy-ARTMAP Classification and Conflict Intersection , 2010, 2010 International Conference on Broadband, Wireless Computing, Communication and Applications.

[68]  M. Lennon,et al.  Spectral unmixing of hyperspectral images with the independent component analysis and wavelet packets , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[69]  A. Pentland Finding the illuminant direction , 1982 .

[70]  Katsushi Ikeuchi,et al.  Light source position and reflectance estimation from a single view without the distant illumination assumption , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[71]  J. Gillis,et al.  Matrix Iterative Analysis , 1961 .

[72]  B. Hapke Theory of reflectance and emittance spectroscopy , 1993 .

[73]  V. P. Pauca,et al.  Nonnegative matrix factorization for spectral data analysis , 2006 .

[74]  Lawrence B. Wolff,et al.  Polarization vision: a new sensory approach to image understanding , 1997, Image Vis. Comput..

[75]  C. Hawryshyn,et al.  Ultraviolet polarization vision in fishes: possible mechanisms for coding e-vector. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[76]  Lawrence B. Wolff,et al.  Polarization-Based Material Classification from Specular Reflection , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[77]  Warren L. Butler,et al.  HIGHER DERIVATIVE ANALYSIS OF COMPLEX ABSORPTION SPECTRA , 1970 .

[78]  P. Gong,et al.  Spectral Feature Extraction of Hyperspectral Images Using Wavelet Transform , 2006 .

[79]  J. Boardman,et al.  Discrimination among semi-arid landscape endmembers using the Spectral Angle Mapper (SAM) algorithm , 1992 .

[80]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[81]  William D. Philpot,et al.  Yellowness index: An application of spectral second derivatives to estimate chlorosis of leaves in stressed vegetation , 1999 .

[82]  K. Torrance,et al.  Polarization, Directional Distribution, and Off-Specular Peak Phenomena in Light Reflected from Roughened Surfaces , 1966 .

[83]  James E. Harvey,et al.  Modified Beckmann-Kirchoff scattering theory for nonparaxial angles , 1998, Optics & Photonics.

[84]  Ronen Basri,et al.  Comparing images under variable illumination , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[85]  Nirmal Keshava,et al.  A Survey of Spectral Unmixing Algorithms , 2003 .

[86]  Katsushi Ikeuchi,et al.  Polarization-based inverse rendering from a single view , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[87]  J. Franklin,et al.  Biomass distribution mapping using airborne digital video imagery and spatial statistics in a semi-arid environment , 1996 .

[88]  Jin Chen,et al.  Generalization of Subpixel Analysis for Hyperspectral Data With Flexibility in Spectral Similarity Measures , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[89]  Theo Gevers,et al.  Detection and Classification of Hyper-Spectral Edges , 1999, BMVC.

[90]  J. Hogg Quantitative remote sensing of land surfaces , 2004 .

[91]  E. T. Y. Lee,et al.  Choosing nodes in parametric curve interpolation , 1989 .

[92]  David Nistér,et al.  Scalable Recognition with a Vocabulary Tree , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[93]  B A Wandell,et al.  Linear models of surface and illuminant spectra. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[94]  David A. Landgrebe,et al.  HYPERSPECTRAL DATA ANALYSIS AND FEATURE REDUCTION VIA PROJECTION PURSUIT , 1999 .

[95]  Edwin R. Hancock,et al.  Skin reflectance modelling for face recognition , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[96]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[97]  Andreas G. Andreou,et al.  Liquid crystal polarization camera , 1997, IEEE Trans. Robotics Autom..

[98]  Zhenwen Dai,et al.  Polygonal Light Source Estimation , 2009, ACCV.

[99]  Jun Zhou,et al.  An affine Invariant hyperspectral texture descriptor based upon heavy-tailed distributions and fourier analysis , 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[100]  C.E. Shannon,et al.  Communication in the Presence of Noise , 1949, Proceedings of the IRE.

[101]  Zhouyu Fu,et al.  Specular Free Spectral Imaging Using Orthogonal Subspace Projection , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[102]  Gary A. Atkinson,et al.  Recovery of surface orientation from diffuse polarization , 2006, IEEE Transactions on Image Processing.

[103]  Andreas G. Andreou,et al.  Polarization camera sensors , 1995, Image Vis. Comput..

[104]  Antonio J. Plaza,et al.  Recent developments in sparse hyperspectral unmixing , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[105]  S. J. Sutley,et al.  Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems , 2003 .

[106]  M. Land,et al.  The Compound Eyes of Mantis Shrimps (Crustacea, Hoplocarida, Stomatopoda). I. Compound Eye Structure: The Detection of Polarized Light , 1991 .

[107]  Berthold K. P. Horn,et al.  Shape from shading , 1989 .

[108]  Carl de Boor,et al.  A Practical Guide to Splines , 1978, Applied Mathematical Sciences.

[109]  Dmitry B. Goldgof,et al.  A Simple Strategy for Calibrating the Geometry of Light Sources , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[110]  A. Atiya,et al.  Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2005, IEEE Transactions on Neural Networks.

[111]  José M. Bioucas-Dias,et al.  Vertex component analysis: a fast algorithm to unmix hyperspectral data , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[112]  I. Nikolov,et al.  Analysis of the dispersion of optical plastic materials , 2007 .

[113]  Patrik O. Hoyer,et al.  Non-negative Matrix Factorization with Sparseness Constraints , 2004, J. Mach. Learn. Res..

[114]  Yang Wang,et al.  Estimation of Multiple Illuminants from a Single Image of Arbitrary Known Geometry , 2002, ECCV.

[115]  Takeshi Shakunaga,et al.  Direct Bundle Estimation for Recovery of Shape, Reflectance Property and Light Position , 2008, ECCV.

[116]  Michael Isard,et al.  Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[117]  Abhishek Kumar Jha,et al.  Affine theorem for two-dimensional Fourier transform , 1993 .

[118]  Dietrich Lehmann,et al.  Nonsmooth nonnegative matrix factorization (nsNMF) , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[119]  R. Clark,et al.  Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications , 1984 .

[120]  David A. Landgrebe,et al.  Toward an optimal supervised classifier for the analysis of hyperspectral data , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[121]  Ondrej Drbohlav,et al.  Unambigous Determination of Shape from Photometric Stereo with Unknown Light Sources , 2001, ICCV.

[122]  S. Asmussen,et al.  Rare events simulation for heavy-tailed , 2000 .

[123]  Dustin Boswell,et al.  Introduction to Support Vector Machines , 2002 .

[124]  F. Goudail,et al.  Target detection with a liquid-crystal-based passive Stokes polarimeter. , 2004, Applied optics.

[125]  Nianjun Liu,et al.  Boosted Band Ratio Feature Selection for Hyperspectral Image Classification , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[126]  Chong-Yung Chi,et al.  A Convex Analysis-Based Minimum-Volume Enclosing Simplex Algorithm for Hyperspectral Unmixing , 2009, IEEE Transactions on Signal Processing.

[127]  Lawrence B. Wolff,et al.  Using polarization to separate reflection components , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[128]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[129]  Bernhard E. Boser,et al.  A training algorithm for optimal margin classifiers , 1992, COLT '92.

[130]  Sam C. Saunders,et al.  Analysis of Dispersion , 2007 .

[131]  Y. Katznelson An Introduction to Harmonic Analysis: Interpolation of Linear Operators , 1968 .

[132]  Andrew Zisserman,et al.  A Visual Vocabulary for Flower Classification , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[133]  Edwin R. Hancock,et al.  Recovery of Surface Height Using Polarization from Two Views , 2005, CAIP.

[134]  Seung-Jean Kim,et al.  Hyperspectral Image Unmixing via Alternating Projected Subgradients , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[135]  Sen Jia,et al.  Spectral and Spatial Complexity-Based Hyperspectral Unmixing , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[136]  Bernhard Schölkopf,et al.  Kernel Principal Component Analysis , 1997, ICANN.

[137]  Alexei A. Efros,et al.  Discovering objects and their location in images , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[138]  Katsushi Ikeuchi,et al.  Stability issues in recovering illumination distribution from brightness in shadows , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[139]  Shree K. Nayar,et al.  Generalization of the Lambertian model and implications for machine vision , 1995, International Journal of Computer Vision.

[140]  P. Beckmann,et al.  The scattering of electromagnetic waves from rough surfaces , 1963 .

[141]  Adrian J. Brown Spectral curve fitting for automatic hyperspectral data analysis , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[142]  Cong Phuoc Huynh,et al.  A NURBS-based spectral reflectance descriptor with applications in computer vision and pattern recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[143]  J. S. Hall Some Polarization Measurements in Astronomy , 1951 .

[144]  Michael D. Steven,et al.  High resolution derivative spectra in remote sensing , 1990 .

[145]  Firooz A. Sadjadi,et al.  Remote sensing using passive infrared Stokes parameters , 2004 .

[146]  Robert J. Woodham,et al.  A Cooperative Algorithm for Determining Surface Orientation from a Single View , 1977, IJCAI.

[147]  Stefan Rahmann,et al.  Inferring 3D scene structure from a single polarization image , 1999, Industrial Lasers and Inspection.

[148]  Steven A. Shafer,et al.  Using color to separate reflection components , 1985 .

[149]  Sang Wook Lee,et al.  Using chromaticity distributions and eigenspace analysis for pose-, illumination-, and specularity-invariant recognition of 3D objects , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[150]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[151]  P. Paatero Least squares formulation of robust non-negative factor analysis , 1997 .

[152]  Carle M. Pieters,et al.  Deconvolution of mineral absorption bands: An improved approach , 1990 .

[153]  R HancockEdwin,et al.  Shape Estimation Using Polarization and Shading from Two Views , 2007 .

[154]  Edwin R. Hancock,et al.  Shape Estimation Using Polarization and Shading from Two Views , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[155]  Keinosuke Fukunaga,et al.  Introduction to statistical pattern recognition (2nd ed.) , 1990 .

[156]  Wei Zhou,et al.  A unified framework for scene illuminant estimation , 2008, Image Vis. Comput..

[157]  Jianbo Shi,et al.  Shape from Shading: Recognizing the Mountains through a Global View , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[158]  Christophe Schlick,et al.  An Inexpensive BRDF Model for Physically‐based Rendering , 1994, Comput. Graph. Forum.

[159]  Jieping Ye,et al.  LDA/QR: an efficient and effective dimension reduction algorithm and its theoretical foundation , 2004, Pattern Recognit..

[160]  Stefan Rahmann,et al.  Reconstruction of specular surfaces using polarization imaging , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[161]  Elli Angelopoulou,et al.  Multispectral skin color modeling , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[162]  Brian A. Wandell,et al.  Dictionaries for sparse representation and recovery of reflectances , 2009, Electronic Imaging.

[163]  Katsushi Ikeuchi,et al.  Separating reflection components based on chromaticity and noise analysis , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[164]  Kwan-Yee Kenneth Wong,et al.  Recovering Light Directions and Camera Poses from a Single Sphere , 2008, ECCV.

[165]  Elli Angelopoulou,et al.  Objective Colour from Multispectral Imaging , 2000, ECCV.

[166]  H. D. Brunk,et al.  AN EMPIRICAL DISTRIBUTION FUNCTION FOR SAMPLING WITH INCOMPLETE INFORMATION , 1955 .

[167]  J. Parkkinen,et al.  Characteristic spectra of Munsell colors , 1989 .

[168]  E. Jaynes Information Theory and Statistical Mechanics , 1957 .

[169]  Andrzej Cichocki,et al.  Nonnegative Matrix and Tensor Factorization T , 2007 .

[170]  Robert J. Woodham,et al.  Photometric method for determining surface orientation from multiple images , 1980 .

[171]  Reiner Lenz,et al.  The Hyperbolic Geometry of Illumination-Induced Chromaticity Changes , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[172]  P. Atkinson,et al.  Cokriging with airborne MSS imagery , 1994 .

[173]  Q. Stout Optimal Algorithms for Unimodal Regression , 2000 .

[174]  L. Maloney Evaluation of linear models of surface spectral reflectance with small numbers of parameters. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[175]  Shree K. Nayar,et al.  Separation of Reflection Components Using Color and Polarization , 1997, International Journal of Computer Vision.

[176]  Qi Wang,et al.  Noise-robust subband decomposition blind signal separation for hyperspectral unmixing , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[177]  Edwin R. Hancock,et al.  Multi-view surface reconstruction using polarization , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[178]  E. Adelson,et al.  Recognition of Surface Reflectance Properties from a Single Image under Unknown Real-World Illumination , 2001 .

[179]  David A. Landgrebe,et al.  Hyperspectral image data analysis , 2002, IEEE Signal Process. Mag..

[180]  Edwin R. Hancock,et al.  New Constraints on Data-Closeness and Needle Map Consistency for Shape-from-Shading , 1999, IEEE Trans. Pattern Anal. Mach. Intell..