Pattern Recognition Letters
Retrieving Multispectral Satellite Images Using Physics-Based Invariant Representations
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
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Color measurements with a consumer digital camera using spectral estimation techniques
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Computing illumination-invariant descriptors of spatially filtered color image regions
IEEE Transactions on Image Processing
Affine illumination compensation on hyperspectral/multiangular remote sensing images
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
Moment invariants to affine transformation of colours
Pattern Recognition Letters
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We apply a general form of affine transformation model to compensate illumination variations in a series of multispectral images of a static scene and compare it to a particular affine and a diagonal transformation models. These models operate in the original multispectral space or in a lower-dimensional space obtained by Singular Value Decomposition (SVD) of the set of images. We use a system consisting of a multispectral camera and a light dome that allows the measurement of multispectral data under carefully controlled illumination conditions to generate a series of multispectral images of a static scene under varying illumination conditions. We evaluate the compensation performance using the CIELAB colour difference between images. The experiments show that the first 2 models perform satisfactorily in the original and lower dimensional spaces.