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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chakrabarti, A. Hirakawa, K. Zickler, T. |
| Copyright Year | 1979 |
| Abstract | We introduce an efficient maximum likelihood approach for one part of the color constancy problem: removing from an image the color cast caused by the spectral distribution of the dominating scene illuminant. We do this by developing a statistical model for the spatial distribution of colors in white balanced images (i.e., those that have no color cast), and then using this model to infer illumination parameters as those being most likely under our model. The key observation is that by applying spatial band-pass filters to color images one unveils color distributions that are unimodal, symmetric, and well represented by a simple parametric form. Once these distributions are fit to training data, they enable efficient maximum likelihood estimation of the dominant illuminant in a new image, and they can be combined with statistical prior information about the illuminant in a very natural manner. Experimental evaluation on standard data sets suggests that the approach performs well. |
| Sponsorship | IEEE Computer Society |
| Page Count | 11 |
| File Size | 3589299 |
| Starting Page | 1509 |
| Ending Page | 1519 |
| File Format | |
| ISSN | 01628828 |
| Volume Number | 34 |
| Issue Number | 8 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-08-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image color analysis Color Maximum likelihood estimation Covariance matrix Training Lighting illumination statistics. Color constancy statistical modeling spatial correlations maximum likelihood |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Computational Theory and Mathematics Computer Vision and Pattern Recognition Software |
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