2017MNRAS.471.3443S

Accurate photometric calibration of optical data is crucial for photometric redshift estimation. We present the Softassign Procrustes Matching (SPM) method to improve the colour calibration upon the commonly used Stellar Locus Regression (SLR) method for the COMBO-17 survey. Our colour calibration approach can be categorised as a point-set matching method, which is frequently used in medical imaging and pattern recognition. We attain a photometric redshift precision Δz/(1 + z_s) of better than 2 per cent. Our method is based on aligning the stellar locus of the uncalibrated stars to that of a spectroscopic sample of the Sloan Digital Sky Survey standard stars. We achieve our goal by finding a correspondence matrix between the two point-sets and applying the matrix to estimate the appropriate translations in multidimensional colour space. The SPM method is able to find the translation between two point-sets, despite the existence of noise and incompleteness of the common structures in the sets, as long as there is a distinct structure in at least one of the colour-colour pairs. We demonstrate the precision of our colour calibration method with a mock catalogue. The SPM colour calibration code is publicly available at https://neuronphysics@bitbucket.org/neuronphysics/spm.git.