@incollection{uea66501,
           month = {October},
          author = {Raja Bala and Graham Finlayson and Chul Lee},
       booktitle = {Handbook of Convex Optimization Methods in Imaging Science},
          editor = {Vishal Monga},
           title = {Computational Color Imaging},
       publisher = {Springer},
            year = {2017},
             doi = {10.1007/978-3-319-61609-4\_3},
           pages = {43--70},
             url = {https://ueaeprints.uea.ac.uk/id/eprint/66501/},
        abstract = {Color quality and fidelity are fundamental considerations in today?s digital imaging systems. Optimization of a color imaging system is a multifaceted problem involving deep understanding of device physics, light-surface interactions, human visual perception, and computational mathematics. The design of a successful color imaging system that meets the desired performance, reliability and cost evokes many interesting and challenging optimization problems. This chapter explores a variety of optimization frameworks that have been developed for color capture, display, and printing. For each device genre, a broad introduction to challenges in color imaging is first presented, followed by a detailed exposition of selected optimization problems and their solutions. Practical considerations such as computational cost, noise containment, and power consumption are introduced as mathematical constraints into the given optimization problem. The chapter concludes with suggestions for future work in this domain.}
}

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