The variational approach to shape from shading
Computer Vision, Graphics, and Image Processing
A novel algorithm for color constancy
International Journal of Computer Vision
A physical approach to color image understanding
International Journal of Computer Vision
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curvature consistency improves local shading analysis
CVGIP: Image Understanding
Surface shape and curvature scales
Image and Vision Computing
Reflectance based object recognition
International Journal of Computer Vision
New Constraints on Data-Closeness and Needle Map Consistency for Shape-from-Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color by Correlation: A Simple, Unifying Framework for Color Constancy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Vision
Solving for Colour Constancy using a Constrained Dichromatic Reflection Model
International Journal of Computer Vision
Pairwise Data Clustering by Deterministic Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Highlight Removal Using Shape-from-Shading
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Object recognition using invariant profiles
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Shape and Source from Shading
Ill-Posed Problems and Regularization Analysis in Early Vision
Ill-Posed Problems and Regularization Analysis in Early Vision
A Class of Photometric Invariants: Separating Material from Shape and Illumination
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Convex Optimization
Separating Reflection Components Based on Chromaticity and Noise Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skin Segmentation Using Color Pixel Classification: Analysis and Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Combined Physical and Statistical Approach to Colour Constancy
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Relief Texture from Specularities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gamut Constrained Illuminant Estimation
International Journal of Computer Vision
Color Subspaces as Photometric Invariants
International Journal of Computer Vision
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Specularity removal in images and videos: a PDE approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Improving gamut mapping color constancy
IEEE Transactions on Image Processing
A comparison of computational color constancy Algorithms. II. Experiments with image data
IEEE Transactions on Image Processing
Colour matching function learning
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
An optimisation approach to the recovery of reflection parameters from a single hyperspectral image
Computer Vision and Image Understanding
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In this paper, we address the problem of photometric invariance in multispectral imaging making use of an optimisation approach based upon the dichromatic model. In this manner, we cast the problem of recovering the spectra of the illuminant, the surface reflectance and the shading and specular factors in a structural optimisation setting. Making use of the additional information provided by multispectral imaging and the structure of image patches, we recover the dichromatic parameters of the scene. To do this, we formulate a target cost function combining the dichromatic error and the smoothness priors for the surfaces under study. The dichromatic parameters are recovered through minimising this cost function in a coordinate descent manner. The algorithm is quite general in nature, admitting the enforcement of smoothness constraints and extending in a straightforward manner to trichromatic settings. Moreover, the objective function is convex with respect to the subset of variables to be optimised in each alternating step of the minimisation strategy. This gives rise to an optimal closed-form solution for each of the iterations in our algorithm. We illustrate the effectiveness of our method for purposes of illuminant spectrum recovery, skin recognition, material clustering and specularity removal. We also compare our results to a number of alternatives.