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In this paper, we propose a spectroscopy based Stellar Color Regression (SCR)method to perform accurate color calibration for modern imaging surveys, takingadvantage of millions of stellar spectra now available. The method isstraightforward, insensitive to systematic errors in the spectroscopicallydetermined stellar atmospheric parameters, applicable to regions that areeffectively covered by spectroscopic surveys, and capable of delivering anaccuracy of a few millimagnitudes for color calibration. As an illustration, wehave applied the method to the SDSS Stripe 82 data (Ivezic et al; I07hereafter). With a total number of 23,759 spectroscopically targeted stars, wehave mapped out the small but strongly correlated color zero point errorspresent in the photometric catalog of Stripe 82, and improve the colorcalibration by a factor of 2 -- 3. Our study also reveals some small butsignificant magnitude dependence errors in z-band for some CCDs. Such errorsare likely to be present in all the SDSS photometric data. Our results arecompared with those from a completely independent test based on the intrinsiccolors of red galaxies presented by I07. The comparison as well as other testsshows that the SCR method has achieved a color calibration internallyconsistent at a level of about 5 mmag in u-g, 3 mmag in g-r, and 2 mmag in r-iand i-z, respectively. Given the power of the SCR method, we discuss brieflythe potential benefits by applying the method to existing, on-going, andup-coming imaging surveys.

Stellar color regression: a spectroscopy based method for color calibration to a few mmag accuracy and the recalibration of Stripe 82