We investigate the natural requirement that an automated contrast enhancement algorithm be idempotent. We show that in a restricted but natural setting, it leads to a binding of the contrast changes with the decision procedure. We obtain: a natural decision procedure for the standard gamma-transformations; a class of contrast changes generalizing these; a procedure to "learn" an algorithm from a set of good images.


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    Title :

    Idempotence and automatic linear contrast enhancements


    Contributors:
    Buzzi, J. (author) / Guichard, F. (author)


    Publication date :

    2005-01-01


    Size :

    400529 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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