A method for computing spectral reflectance
Biological Cybernetics
Wavelength selection for synthetic image generation
Computer Vision, Graphics, and Image Processing
A novel algorithm for color constancy
International Journal of Computer Vision
Color constancy from mutual reflection
International Journal of Computer Vision
Surface Identification Using the Dichromatic Reflection Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Precision requirements for digital color reproduction
ACM Transactions on Graphics (TOG)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color constancy for scenes with varying illumination
Computer Vision and Image Understanding - Special issue on physics-based modeling and reasoning in computer vision
Colour Model Selection and Adaption in Dynamic Scenes
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Color by Correlation: A Simple, Unifying Approach to Color Constancy
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Tracking regions of human skin through illumination changes
Pattern Recognition Letters - Special issue: Colour image processing and analysis
Spectral Filter Optimization for the Recovery of Parameters which Describe Human Skin
IEEE Transactions on Pattern Analysis and Machine Intelligence
Separating Reflection Components Based on Chromaticity and Noise Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Modelling and segmentation of colour images in polar representations
Image and Vision Computing
Dichromatic illumination estimation without pre-segmentation
Pattern Recognition Letters
A color topographic map based on the dichromatic reflectance model
Journal on Image and Video Processing - Color in Image and Video Processing
Proceedings of the 2008 ACM symposium on Virtual reality software and technology
A Solution of the Dichromatic Model for Multispectral Photometric Invariance
International Journal of Computer Vision
Body color sets: A compact and reliable representation of images
Journal of Visual Communication and Image Representation
Illumination chromaticity estimation using inverse-intensity chromaticity space
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
On determining the color of the illuminant using the dichromatic reflection model
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Correspondence search in the presence of specular highlights using specular-free two-band images
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Illuminant estimation from projections on the planckian locus
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
Colour matching function learning
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
A biologically motivated double-opponency approach to illumination invariance
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
A view-invariant and anti-reflection algorithm for car body extraction and color classification
Multimedia Tools and Applications
An optimisation approach to the recovery of reflection parameters from a single hyperspectral image
Computer Vision and Image Understanding
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Statistics-based colour constancy algorithms work well as long as there are many colours in a scene, they fail however when the encountering scenes comprise few surfaces. In contrast, physics-based algorithms, based on an understanding of physical processes such as highlights and interreflections, are theoretically able to solve for colour constancy even when there are as few as two surfaces in a scene. Unfortunately, physics-based theories rarely work outside the lab. In this paper we show that a combination of physical and statistical knowledge leads to a surprisingly simple and powerful colour constancy algorithm, one that also works well for images of natural scenes.From a physical standpoint we observe that given the dichromatic model of image formation the colour signals coming from a single uniformly-coloured surface are mapped to a line in chromaticity space. One component of the line is defined by the colour of the illuminant (i.e. specular highlights) and the other is due to its matte, or Lambertian, reflectance. We then make the statistical observation that the chromaticities of common light sources all follow closely the Planckian locus of black-body radiators. It follows that by intersecting the dichromatic line with the Planckian locus we can estimate the chromaticity of the illumination. We can solve for colour constancy even when there is a single surface in the scene. When there are many surfaces in a scene the individual estimates from each surface are averaged together to improve accuracy.In a set of experiments on real images we show our approach delivers very good colour constancy. Moreover, performance is significantly better than previous dichromatic algorithms.