@article{uea48825,
          volume = {40},
          number = {3},
           month = {June},
          author = {Graham D. Finlayson and Maryam Mohammadzadeh Darrodi and Michal Mackiewicz},
            note = {{\copyright} 2014 The Authors Color Research \& Application Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.},
           title = {The alternating least squares technique for nonuniform intensity color correction},
            year = {2015},
         journal = {Color Research \& Application},
             doi = {10.1002/col.21889},
           pages = {232?242},
        keywords = {color correction,nonuniform intensity,alternating least squares,characterization,shading field},
             url = {https://ueaeprints.uea.ac.uk/id/eprint/48825/},
        abstract = {Color correction involves mapping device RGBs to display counterparts or to corresponding XYZs. A popular methodology is to take an image of a color chart and then solve for the best 3 {$\times$} 3 matrix that maps the RGBs to the corresponding known XYZs. However, this approach fails at times when the intensity of the light varies across the chart. This variation needs to be removed before estimating the correction matrix. This is typically achieved by acquiring an image of a uniform gray chart in the same location, and then dividing the color checker image by the gray-chart image. Of course, taking images of two charts doubles the complexity of color correction. In this article, we present an alternative color correction algorithm that simultaneously estimates the intensity variation and the 3 {$\times$} 3 transformation matrix from a single image of a color chart. We show that the color correction problem, that is, finding the 3 {$\times$} 3 correction matrix, can be solved using a simple alternating least-squares procedure. Experiments validate our approach. {\copyright} 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 232?242, 2015}
}

{"_id":"9md7bHQPz8YvfPze4","bibbaseid":"finlayson-darrodi-mackiewicz-thealternatingleastsquarestechniquefornonuniformintensitycolorcorrection-2015","author_short":["Finlayson, G. D.","Darrodi, M. M.","Mackiewicz, M."],"bibdata":{"bibtype":"article","type":"article","volume":"40","number":"3","month":"June","author":[{"firstnames":["Graham","D."],"propositions":[],"lastnames":["Finlayson"],"suffixes":[]},{"firstnames":["Maryam","Mohammadzadeh"],"propositions":[],"lastnames":["Darrodi"],"suffixes":[]},{"firstnames":["Michal"],"propositions":[],"lastnames":["Mackiewicz"],"suffixes":[]}],"note":"o̧pyright 2014 The Authors Color Research & Application Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.","title":"The alternating least squares technique for nonuniform intensity color correction","year":"2015","journal":"Color Research & Application","doi":"10.1002/col.21889","pages":"232?242","keywords":"color correction,nonuniform intensity,alternating least squares,characterization,shading field","url":"https://ueaeprints.uea.ac.uk/id/eprint/48825/","abstract":"Color correction involves mapping device RGBs to display counterparts or to corresponding XYZs. A popular methodology is to take an image of a color chart and then solve for the best 3 $\\times$ 3 matrix that maps the RGBs to the corresponding known XYZs. However, this approach fails at times when the intensity of the light varies across the chart. This variation needs to be removed before estimating the correction matrix. This is typically achieved by acquiring an image of a uniform gray chart in the same location, and then dividing the color checker image by the gray-chart image. Of course, taking images of two charts doubles the complexity of color correction. In this article, we present an alternative color correction algorithm that simultaneously estimates the intensity variation and the 3 $\\times$ 3 transformation matrix from a single image of a color chart. We show that the color correction problem, that is, finding the 3 $\\times$ 3 correction matrix, can be solved using a simple alternating least-squares procedure. Experiments validate our approach. o̧pyright 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 232?242, 2015","bibtex":"@article{uea48825,\n volume = {40},\n number = {3},\n month = {June},\n author = {Graham D. Finlayson and Maryam Mohammadzadeh Darrodi and Michal Mackiewicz},\n note = {{\\copyright} 2014 The Authors Color Research \\& Application Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.},\n title = {The alternating least squares technique for nonuniform intensity color correction},\n year = {2015},\n journal = {Color Research \\& Application},\n doi = {10.1002/col.21889},\n pages = {232?242},\n keywords = {color correction,nonuniform intensity,alternating least squares,characterization,shading field},\n url = {https://ueaeprints.uea.ac.uk/id/eprint/48825/},\n abstract = {Color correction involves mapping device RGBs to display counterparts or to corresponding XYZs. A popular methodology is to take an image of a color chart and then solve for the best 3 {$\\times$} 3 matrix that maps the RGBs to the corresponding known XYZs. However, this approach fails at times when the intensity of the light varies across the chart. This variation needs to be removed before estimating the correction matrix. This is typically achieved by acquiring an image of a uniform gray chart in the same location, and then dividing the color checker image by the gray-chart image. Of course, taking images of two charts doubles the complexity of color correction. In this article, we present an alternative color correction algorithm that simultaneously estimates the intensity variation and the 3 {$\\times$} 3 transformation matrix from a single image of a color chart. We show that the color correction problem, that is, finding the 3 {$\\times$} 3 correction matrix, can be solved using a simple alternating least-squares procedure. Experiments validate our approach. {\\copyright} 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 232?242, 2015}\n}\n\n","author_short":["Finlayson, G. D.","Darrodi, M. 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