Retrieving Multispectral Satellite Images Using Physics-Based Invariant Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
MLESAC: a new robust estimator with application to estimating image geometry
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Moment invariants for recognition under changing viewpoint and illumination
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
An Illumination Independent Eye Detection Algorithm
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Invariant salient regions based image retrieval under viewpoint and illumination variations
Journal of Visual Communication and Image Representation
Groupwise Geometric and Photometric Direct Image Registration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized least squares-based parametric motion estimation
Computer Vision and Image Understanding
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The estimation of parametric global motion has had a significant attention during the last two decades, but despite the great efforts invested, there are still open issues. One of the most important ones is related to the ability to simultaneously cope with viewpoint and illumination changes while keeping the method accurate. In this paper, a Generalized least squared-based motion estimator model able to cope with large geometric transformations and illumination changes is presented. Experiments are made on a series of images showing that the presented technique provides accurate estimates of the motion and illumination parameters.