We introduce a method for producing a galaxy sample unbiased by surface brightness and stellar mass , by selecting star-forming galaxies via the positions of core-collapse supernovae ( CCSNe ) .
Whilst matching \sim 2400 supernovae from the SDSS-II Supernova Survey to their host galaxies using IAC Stripe 82 legacy coadded imaging , we find \sim 150 previously unidentified low surface brightness galaxies ( LSBGs ) .
Using a sub-sample of \sim 900 CCSNe , we infer CCSN-rate and star-formation rate densities as a function of galaxy stellar mass , and the star-forming galaxy stellar mass function .
Resultant star-forming galaxy number densities are found to increase following a power-law down to our low mass limit of \sim 10 ^ { 6.4 } M _ { \odot } by a single Schechter function with a faint-end slope of \alpha = -1.41 .
Number densities are consistent with those found by the EAGLE simulations invoking a \Lambda -CDM cosmology .
Overcoming surface brightness and stellar mass biases is important for assessment of the sub-structure problem .
In order to estimate galaxy stellar masses , a new code for the calculation of galaxy photometric redshifts , zMedIC , is also presented , and shown to be particularly useful for small samples of galaxies .