Color constancy from mutual reflection
International Journal of Computer Vision
Highly parallel computing (2nd ed.)
Highly parallel computing (2nd ed.)
Machine vision
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
Robot Vision
Digital Image Processing
Comprehensive Colour Image Normalization
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Is Machine Colour Constancy Good Enough?
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Evolving Color Constancy for an Artificial Retina
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
A multistage neural network for color constancy and color induction
IEEE Transactions on Neural Networks
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Estimating the color of the illuminant using anisotropic diffusion
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
How does the brain arrive at a color constant descriptor?
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
On determining the color of the illuminant using the dichromatic reflection model
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
A linear system form solution to compute the local space average color
Machine Vision and Applications
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Objects retain their color in spite of changes in the wavelength and energy composition of the light they reflect. This phenomenon is called color constancy and plays an important role in computer vision research. We have devised a parallel algorithm for color constancy. The algorithm runs on a two-dimensional grid of processors each of which can exchange information with its four neighboring processors. Each processor calculates local average color. This information is then used to estimate the reflectances of the object. The algorithm was tested on several images of everyday objects. The algorithm also works for scenes where the illuminant changes smoothly over the image.